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{"repo": "aymericdamien/topdeeplearning", "files": {"README.md": {"e0492092372fa6ce31fdb99af4c13c5b347fcb81": {"t": 1785595272.043359, "n": 309716, "h": "e9a301d38336acff", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2026.07.14\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[openclaw](https://github.com/openclaw/openclaw)|383k|Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞|\n|[superpowers](https://github.com/obra/superpowers)|255k|An agentic skills framework & software development methodology that works.|\n|[ECC](https://github.com/affaan-m/ECC)|230k|The agent harness performance optimization system. Skills, instincts, memory, security, and researc…|\n|[hermes-agent](https://github.com/NousResearch/hermes-agent)|215k|The agent that grows with you|\n|[n8n](https://github.com/n8n-io/n8n)|196k|Fair-code workflow automation platform with native AI capabilities. Combine visual building with cu…|\n|[tensorflow](https://github.com/tensorflow/tensorflow)|196k|An Open Source Machine Learning Framework for Everyone|\n|[claw-code](https://github.com/ultraworkers/claw-code)|195k|An agent-managed museum exhibit, built in Rust with Gajae-Code / LazyCodex — developed and maintain…|\n|[opencode](https://github.com/anomalyco/opencode)|186k|The open source coding agent.|\n|[AutoGPT](https://github.com/Significant-Gravitas/AutoGPT)|186k|AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to prov…|\n|[ollama](https://github.com/ollama/ollama)|176k|Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other model…|\n|[skills](https://github.com/mattpocock/skills)|170k|Skills for Real Engineers. Straight from my .claude directory.|\n|[markitdown](https://github.com/microsoft/markitdown)|166k|Python tool for converting files and office documents to Markdown.|\n|[prompts.chat](https://github.com/f/prompts.chat)|166k|f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and o…|\n|[stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)|164k|Stable Diffusion web UI|\n|[transformers](https://github.com/huggingface/transformers)|163k|🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text…|\n|[skills](https://github.com/anthropics/skills)|161k|Public repository for Agent Skills|\n|[JavaGuide](https://github.com/Snailclimb/JavaGuide)|157k|Java 面试 & 后端通用面试指南，覆盖计算机基础、数据库、分布式、高并发、系统设计与 AI 应用开发|\n|[langflow](https://github.com/langflow-ai/langflow)|152k|Langflow is a powerful tool for building and deploying AI-powered agents and workflows.|\n|[firecrawl](https://github.com/firecrawl/firecrawl)|151k|The API to search, scrape, and interact with the web at scale. 🔥|\n|[dify](https://github.com/langgenius/dify)|149k|Production-ready platform for agentic workflow development.|\n|[open-webui](https://github.com/open-webui/open-webui)|145k|User-friendly AI Interface (Supports Ollama, OpenAI API, ...)|\n|[system-prompts-and-models-of-ai-tools](https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools)|142k|FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new,…|\n|[langchain](https://github.com/langchain-ai/langchain)|142k|The agent engineering platform.|\n|[claude-code](https://github.com/anthropics/claude-code)|138k|Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and h…|\n|[agency-agents](https://github.com/msitarzewski/agency-agents)|131k|A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from wh…|\n|[gstack](https://github.com/garrytan/gstack)|122k|Use Garry Tan's exact Claude Code setup: 23 opinionated tools that serve as CEO, Designer, Eng Mana…|\n|[ComfyUI](https://github.com/Comfy-Org/ComfyUI)|121k|The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.|\n|[llama.cpp](https://github.com/ggml-org/llama.cpp)|120k|LLM inference in C/C++|\n|[cc-switch](https://github.com/farion1231/cc-switch)|117k|A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Gemini CL…|\n|[generative-ai-for-beginners](https://github.com/microsoft/generative-ai-for-beginners)|113k|21 Lessons, Get Started Building with Generative AI|\n|[supabase](https://github.com/supabase/supabase)|106k|The Postgres development platform. 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Automate tasks online with ease.|\n|[DeepSeek-V3](https://github.com/deepseek-ai/DeepSeek-V3)|104k||\n|[pytorch](https://github.com/pytorch/pytorch)|102k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[LLMs-from-scratch](https://github.com/rasbt/LLMs-from-scratch)|99.1k|Implement a ChatGPT-like LLM in PyTorch from scratch, step by step|\n|[codex](https://github.com/openai/codex)|98k|Lightweight coding agent that runs in your terminal|\n|[MoneyPrinterTurbo](https://github.com/harry0703/MoneyPrinterTurbo)|97.4k|利用AI大模型，一键生成高清短视频 Generate short videos with one click using AI LLM.|\n|[Deep-Live-Cam](https://github.com/hacksider/Deep-Live-Cam)|94.9k|real time face swap and one-click video deepfake with only a single image|\n|[TradingAgents](https://github.com/TauricResearch/TradingAgents)|93k|TradingAgents: Multi-Agents LLM Financial Trading Framework|\n|[DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1)|92k||\n|[autoresearch](https://github.com/karpathy/autoresearch)|91.1k|AI agents running research on single-GPU nanochat training automatically|\n|[opencv](https://github.com/opencv/opencv)|89.9k|Open Source Computer Vision Library|\n|[caveman](https://github.com/JuliusBrussee/caveman)|89.4k|🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking…|\n|[servers](https://github.com/modelcontextprotocol/servers)|88.5k|Model Context Protocol Servers|\n|[NextChat](https://github.com/ChatGPTNextWeb/NextChat)|88.5k|✨ Light and Fast AI Assistant. Support: Web \\| iOS \\| MacOS \\| Android \\| Linux \\| Windows|\n|[ML-For-Beginners](https://github.com/microsoft/ML-For-Beginners)|88.1k|12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all|\n|[claude-mem](https://github.com/thedotmack/claude-mem)|87.2k|Persistent Context Across Sessions for Every Agent – Captures everything your agent does during ses…|\n|[vllm](https://github.com/vllm-project/vllm)|86.3k|A high-throughput and memory-efficient inference and serving engine for LLMs|\n|[graphify](https://github.com/Graphify-Labs/graphify)|86.1k|AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, Gemini CLI, and more). Turn any fo…|\n|[PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR)|85.5k|Turn any PDF or image document into structured data for your AI. 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The best code is the code you ne…|\n|[funNLP](https://github.com/fighting41love/funNLP)|81.8k|中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文…|\n|[llm-course](https://github.com/mlabonne/llm-course)|80.9k|Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.|\n|[OpenHands](https://github.com/OpenHands/OpenHands)|80.8k|🙌 OpenHands: AI-Driven Development|\n|[RuView](https://github.com/ruvnet/RuView)|80.6k|π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, a…|\n|[lobehub](https://github.com/lobehub/lobehub)|79.8k|🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, sche…|\n|[netdata](https://github.com/netdata/netdata)|79.6k|The fastest path to AI-powered full stack observability, even for lean teams.|\n|[d2l-zh](https://github.com/d2l-ai/d2l-zh)|78.9k|《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。|\n|[agent-skills](https://github.com/addyosmani/agent-skills)|78.3k|Production-grade engineering skills for AI coding agents.|\n|[open-design](https://github.com/nexu-io/open-design)|78.1k|🎨 The open-source Claude Design alternative. 🖥️ Local-first desktop app. 🖼️ Your coding agent becom…|\n|[models](https://github.com/tensorflow/models)|77.7k|Models and examples built with TensorFlow|\n|[gpt4all](https://github.com/nomic-ai/gpt4all)|77.4k|GPT4All: Run Local LLMs on Any Device. 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Don't be shy, join here: https://disco…|\n|[daytona](https://github.com/daytonaio/daytona)|72.2k|Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code|\n|[gpt_academic](https://github.com/binary-husky/gpt_academic)|71.1k|为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论…|\n|[rtk](https://github.com/rtk-ai/rtk)|71k|CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. 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Create next-gen UI experiences with the protocol and SDK!|\n"}, "97d2ff1922ca6c64a7c32ce67f088950b8591e3a": {"t": 1785772688.5986338, "n": 365379, "h": "f4ecd5d11d2d0154", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2026.07.14\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[ECC](https://github.com/affaan-m/ECC)|230k|The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.|\n|[hermes-agent](https://github.com/NousResearch/hermes-agent)|215k|The agent that grows with you|\n|[tensorflow](https://github.com/tensorflow/tensorflow)|196k|An Open Source Machine Learning Framework for Everyone|\n|[AutoGPT](https://github.com/Significant-Gravitas/AutoGPT)|186k|AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.|\n|[ollama](https://github.com/ollama/ollama)|176k|Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.|\n|[markitdown](https://github.com/microsoft/markitdown)|166k|Python tool for converting files and office documents to Markdown.|\n|[prompts.chat](https://github.com/f/prompts.chat)|166k|f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.|\n|[stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)|164k|Stable Diffusion web UI|\n|[transformers](https://github.com/huggingface/transformers)|163k|🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.|\n|[langflow](https://github.com/langflow-ai/langflow)|152k|Langflow is a powerful tool for building and deploying AI-powered agents and workflows.|\n|[firecrawl](https://github.com/firecrawl/firecrawl)|151k|The API to search, scrape, and interact with the web at scale. 🔥|\n|[dify](https://github.com/langgenius/dify)|149k|Production-ready platform for agentic workflow development.|\n|[open-webui](https://github.com/open-webui/open-webui)|145k|User-friendly AI Interface (Supports Ollama, OpenAI API, ...)|\n|[langchain](https://github.com/langchain-ai/langchain)|142k|The agent engineering platform.|\n|[ComfyUI](https://github.com/Comfy-Org/ComfyUI)|121k|The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.|\n|[llama.cpp](https://github.com/ggml-org/llama.cpp)|120k|LLM inference in C/C++|\n|[generative-ai-for-beginners](https://github.com/microsoft/generative-ai-for-beginners)|113k|21 Lessons, Get Started Building with Generative AI|\n|[supabase](https://github.com/supabase/supabase)|106k|The Postgres development platform. 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The best code is the code you never wrote.|\n|[funNLP](https://github.com/fighting41love/funNLP)|81.8k|中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名人词库、诗词词库、医学词库、饮食词库、法律词库、汽车词库、动物词库、中文聊天语料、中文谣言数据、百度中文问答数据集、句子相似度匹配算法集合、bert资源、文本生成&摘要相关工具、cocoNLP信息抽取工具、国内电话号码正则匹配、清华大学XLORE:中英文跨语言百科知识图谱、清华大学人工智能技术系列报告、自然语言生成、NLU太难了系列、自动对联数据及机器人、用户名黑名单列表、罪名法务名词及分类模型、微信公众号语料、cs224n深度学习自然语言处理课程、中文手写汉字识别、中文自然语言处理 语料/数据集、变量命名神器、分词语料库+代码、任务型对话英文数据集、ASR 语音数据集 + 基于深度学习的中文语音识别系统、笑声检测器、Microsoft多语言数字/单位/如日期时间识别包、中华新华字典数据库及api(包括常用歇后语、成语、词语和汉字)、文档图谱自动生成、SpaCy 中文模型、Common Voice语音识别数据集新版、神经网络关系抽取、基于bert的命名实体识别、关键词(Keyphrase)抽取包pke、基于医疗领域知识图谱的问答系统、基于依存句法与语义角色标注的事件三元组抽取、依存句法分析4万句高质量标注数据、cnocr：用来做中文OCR的Python3包、中文人物关系知识图谱项目、中文nlp竞赛项目及代码汇总、中文字符数据、speech-aligner: 从“人声语音”及其“语言文本”产生音素级别时间对齐标注的工具、AmpliGraph: 知识图谱表示学习(Python)库：知识图谱概念链接预测、Scattertext 文本可视化(python)、语言/知识表示工具：BERT & ERNIE、中文对比英文自然语言处理NLP的区别综述、Synonyms中文近义词工具包、HarvestText领域自适应文本挖掘工具（新词发现-情感分析-实体链接等）、word2word：(Python)方便易用的多语言词-词对集：62种语言/3,564个多语言对、语音识别语料生成工具：从具有音频/字幕的在线视频创建自动语音识别(ASR)语料库、构建医疗实体识别的模型（包含词典和语料标注）、单文档非监督的关键词抽取、Kashgari中使用gpt-2语言模型、开源的金融投资数据提取工具、文本自动摘要库TextTeaser: 仅支持英文、人民日报语料处理工具集、一些关于自然语言的基本模型、基于14W歌曲知识库的问答尝试--功能包括歌词接龙and已知歌词找歌曲以及歌曲歌手歌词三角关系的问答、基于Siamese bilstm模型的相似句子判定模型并提供训练数据集和测试数据集、用Transformer编解码模型实现的根据Hacker News文章标题自动生成评论、用BERT进行序列标记和文本分类的模板代码、LitBank：NLP数据集——支持自然语言处理和计算人文学科任务的100部带标记英文小说语料、百度开源的基准信息抽取系统、虚假新闻数据集、Facebook: LAMA语言模型分析，提供Transformer-XL/BERT/ELMo/GPT预训练语言模型的统一访问接口、CommonsenseQA：面向常识的英文QA挑战、中文知识图谱资料、数据及工具、各大公司内部里大牛分享的技术文档 PDF 或者 PPT、自然语言生成SQL语句（英文）、中文NLP数据增强（EDA）工具、英文NLP数据增强工具 、基于医药知识图谱的智能问答系统、京东商品知识图谱、基于mongodb存储的军事领域知识图谱问答项目、基于远监督的中文关系抽取、语音情感分析、中文ULMFiT-情感分析-文本分类-语料及模型、一个拍照做题程序、世界各国大规模人名库、一个利用有趣中文语料库 qingyun 训练出来的中文聊天机器人、中文聊天机器人seqGAN、省市区镇行政区划数据带拼音标注、教育行业新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增广库、中文全词覆盖BERT及两份阅读理解数据、ConvLab：开源多域端到端对话系统平台、中文自然语言处理数据集、基于最新版本rasa搭建的对话系统、基于TensorFlow和BERT的管道式实体及关系抽取、一个小型的证券知识图谱/知识库、复盘所有NLP比赛的TOP方案、OpenCLaP：多领域开源中文预训练语言模型仓库、UER：基于不同语料+编码器+目标任务的中文预训练模型仓库、中文自然语言处理向量合集、基于金融-司法领域(兼有闲聊性质)的聊天机器人、g2pC：基于上下文的汉语读音自动标记模块、Zincbase 知识图谱构建工具包、诗歌质量评价/细粒度情感诗歌语料库、快速转化「中文数字」和「阿拉伯数字」、百度知道问答语料库、基于知识图谱的问答系统、jieba_fast 加速版的jieba、正则表达式教程、中文阅读理解数据集、基于BERT等最新语言模型的抽取式摘要提取、Python利用深度学习进行文本摘要的综合指南、知识图谱深度学习相关资料整理、维基大规模平行文本语料、StanfordNLP 0.2.0：纯Python版自然语言处理包、NeuralNLP-NeuralClassifier：腾讯开源深度学习文本分类工具、端到端的封闭域对话系统、中文命名实体识别：NeuroNER vs. BertNER、新闻事件线索抽取、2019年百度的三元组抽取比赛：“科学空间队”源码、基于依存句法的开放域文本知识三元组抽取和知识库构建、中文的GPT2训练代码、ML-NLP - 机器学习(Machine Learning)NLP面试中常考到的知识点和代码实现、nlp4han:中文自然语言处理工具集(断句/分词/词性标注/组块/句法分析/语义分析/NER/N元语法/HMM/代词消解/情感分析/拼写检查、XLM：Facebook的跨语言预训练语言模型、用基于BERT的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取、中文自然语言处理相关的开放任务-数据集-当前最佳结果、CoupletAI - 基于CNN+Bi-LSTM+Attention 的自动对对联系统、抽象知识图谱、MiningZhiDaoQACorpus - 580万百度知道问答数据挖掘项目、brat rapid annotation tool: 序列标注工具、大规模中文知识图谱数据：1.4亿实体、数据增强在机器翻译及其他nlp任务中的应用及效果、allennlp阅读理解:支持多种数据和模型、PDF表格数据提取工具 、 Graphbrain：AI开源软件库和科研工具，目的是促进自动意义提取和文本理解以及知识的探索和推断、简历自动筛选系统、基于命名实体识别的简历自动摘要、中文语言理解测评基准，包括代表性的数据集&基准模型&语料库&排行榜、树洞 OCR 文字识别 、从包含表格的扫描图片中识别表格和文字、语声迁移、Python口语自然语言处理工具集(英文)、 similarity：相似度计算工具包，java编写、海量中文预训练ALBERT模型 、Transformers 2.0 、基于大规模音频数据集Audioset的音频增强 、Poplar：网页版自然语言标注工具、图片文字去除，可用于漫画翻译 、186种语言的数字叫法库、Amazon发布基于知识的人-人开放领域对话数据集 、中文文本纠错模块代码、繁简体转换 、 Python实现的多种文本可读性评价指标、类似于人名/地名/组织机构名的命名体识别数据集 、东南大学《知识图谱》研究生课程(资料)、. 英文拼写检查库 、 wwsearch是企业微信后台自研的全文检索引擎、CHAMELEON：深度学习新闻推荐系统元架构 、 8篇论文梳理BERT相关模型进展与反思、DocSearch：免费文档搜索引擎、 LIDA：轻量交互式对话标注工具 、aili - the fastest in-memory index in the East 东半球最快并发索引 、知识图谱车音工作项目、自然语言生成资源大全 、中日韩分词库mecab的Python接口库、中文文本摘要/关键词提取、汉字字符特征提取器 (featurizer)，提取汉字的特征（发音特征、字形特征）用做深度学习的特征、中文生成任务基准测评 、中文缩写数据集、中文任务基准测评 - 代表性的数据集-基准(预训练)模型-语料库-baseline-工具包-排行榜、PySS3：面向可解释AI的SS3文本分类器机器可视化工具 、中文NLP数据集列表、COPE - 格律诗编辑程序、doccano：基于网页的开源协同多语言文本标注工具 、PreNLP：自然语言预处理库、简单的简历解析器，用来从简历中提取关键信息、用于中文闲聊的GPT2模型：GPT2-chitchat、基于检索聊天机器人多轮响应选择相关资源列表(Leaderboards、Datasets、Papers)、(Colab)抽象文本摘要实现集锦(教程 、词语拼音数据、高效模糊搜索工具、NLP数据增广资源集、微软对话机器人框架 、 GitHub Typo Corpus：大规模GitHub多语言拼写错误/语法错误数据集、TextCluster：短文本聚类预处理模块 Short text cluster、面向语音识别的中文文本规范化、BLINK：最先进的实体链接库、BertPunc：基于BERT的最先进标点修复模型、Tokenizer：快速、可定制的文本词条化库、中文语言理解测评基准，包括代表性的数据集、基准(预训练)模型、语料库、排行榜、spaCy 医学文本挖掘与信息提取 、 NLP任务示例项目代码集、 python拼写检查库、chatbot-list - 行业内关于智能客服、聊天机器人的应用和架构、算法分享和介绍、语音质量评价指标(MOSNet, BSSEval, STOI, PESQ, SRMR)、 用138GB语料训练的法文RoBERTa预训练语言模型 、BERT-NER-Pytorch：三种不同模式的BERT中文NER实验、无道词典 - 有道词典的命令行版本，支持英汉互查和在线查询、2019年NLP亮点回顾、 Chinese medical dialogue data 中文医疗对话数据集 、最好的汉字数字(中文数字)-阿拉伯数字转换工具、 基于百科知识库的中文词语多词义/义项获取与特定句子词语语义消歧、awesome-nlp-sentiment-analysis - 情感分析、情绪原因识别、评价对象和评价词抽取、LineFlow：面向所有深度学习框架的NLP数据高效加载器、中文医学NLP公开资源整理 、MedQuAD：(英文)医学问答数据集、将自然语言数字串解析转换为整数和浮点数、Transfer Learning in Natural Language Processing (NLP) 、面向语音识别的中文/英文发音辞典、Tokenizers：注重性能与多功能性的最先进分词器、CLUENER 细粒度命名实体识别 Fine Grained Named Entity Recognition、 基于BERT的中文命名实体识别、中文谣言数据库、NLP数据集/基准任务大列表、nlp相关的一些论文及代码, 包括主题模型、词向量(Word Embedding)、命名实体识别(NER)、文本分类(Text Classificatin)、文本生成(Text Generation)、文本相似性(Text Similarity)计算等，涉及到各种与nlp相关的算法，基于keras和tensorflow 、Python文本挖掘/NLP实战示例、 Blackstone：面向非结构化法律文本的spaCy pipeline和NLP模型通过同义词替换实现文本“变脸” 、中文 预训练 ELECTREA 模型: 基于对抗学习 pretrain Chinese Model 、albert-chinese-ner - 用预训练语言模型ALBERT做中文NER 、基于GPT2的特定主题文本生成/文本增广、开源预训练语言模型合集、多语言句向量包、编码、标记和实现：一种可控高效的文本生成方法、 英文脏话大列表 、attnvis：GPT2、BERT等transformer语言模型注意力交互可视化、CoVoST：Facebook发布的多语种语音-文本翻译语料库，包括11种语言(法语、德语、荷兰语、俄语、西班牙语、意大利语、土耳其语、波斯语、瑞典语、蒙古语和中文)的语音、文字转录及英文译文、Jiagu自然语言处理工具 - 以BiLSTM等模型为基础，提供知识图谱关系抽取 中文分词 词性标注 命名实体识别 情感分析 新词发现 关键词 文本摘要 文本聚类等功能、用unet实现对文档表格的自动检测，表格重建、NLP事件提取文献资源列表 、 金融领域自然语言处理研究资源大列表、CLUEDatasetSearch - 中英文NLP数据集：搜索所有中文NLP数据集，附常用英文NLP数据集 、medical_NER - 中文医学知识图谱命名实体识别 、(哈佛)讲因果推理的免费书、知识图谱相关学习资料/数据集/工具资源大列表、Forte：灵活强大的自然语言处理pipeline工具集 、Python字符串相似性算法库、PyLaia：面向手写文档分析的深度学习工具包、TextFooler：针对文本分类/推理的对抗文本生成模块、Haystack：灵活、强大的可扩展问答(QA)框架、中文关键短语抽取工具|\n|[llm-course](https://github.com/mlabonne/llm-course)|80.9k|Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.|\n|[OpenHands](https://github.com/OpenHands/OpenHands)|80.8k|🙌 OpenHands: AI-Driven Development|\n|[RuView](https://github.com/ruvnet/RuView)|80.6k|π RuView turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — all without a single pixel of video.|\n|[lobehub](https://github.com/lobehub/lobehub)|79.8k|🤯 LobeHub is your Chief Agent Operator, organizing your agents into 7×24 operations by hiring, scheduling, and reporting on your entire AI team.|\n|[netdata](https://github.com/netdata/netdata)|79.6k|The fastest path to AI-powered full stack observability, even for lean teams.|\n|[d2l-zh](https://github.com/d2l-ai/d2l-zh)|78.9k|《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。|\n|[open-design](https://github.com/nexu-io/open-design)|78.1k|🎨 The open-source Claude Design alternative. 🖥️ Local-first desktop app. 🖼️ Your coding agent becomes the design engine: prototypes, landing pages, dashboards, slides, images & video — real files, HTML/PDF/PPTX/MP4 export. 🤖 Claude Code / Codex / Cursor / Gemini / OpenCode / Qwen & 20+ CLIs via BYOK.|\n|[models](https://github.com/tensorflow/models)|77.7k|Models and examples built with TensorFlow|\n|[gpt4all](https://github.com/nomic-ai/gpt4all)|77.4k|GPT4All: Run Local LLMs on Any Device. 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Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.|\n|[airflow](https://github.com/apache/airflow)|46.1k|Apache Airflow - A platform to programmatically author, schedule, and monitor workflows|\n|[Umi-OCR](https://github.com/hiroi-sora/Umi-OCR)|46.1k|OCR software, free and offline. 开源、免费的离线OCR软件。支持截屏/批量导入图片，PDF文档识别，排除水印/页眉页脚，扫描/生成二维码。内置多国语言库。|\n|[CowAgent](https://github.com/zhayujie/CowAgent)|46k|Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-model, multi-channel. Lightweight, extensible, one-line install. 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Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more|\n|[OpenVoice](https://github.com/myshell-ai/OpenVoice)|36.9k|Instant voice cloning by MIT and MyShell. Audio foundation model.|\n|[MockingBird](https://github.com/babysor/MockingBird)|36.9k|🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time|\n|[rufus](https://github.com/pbatard/rufus)|36.9k|The Reliable USB Formatting Utility|\n|[ai-engineering-hub](https://github.com/patchy631/ai-engineering-hub)|36.5k|In-depth tutorials on LLMs, RAGs and real-world AI agent applications.|\n|[HanLP](https://github.com/hankcs/HanLP)|36.5k|Natural Language Processing for the next decade. Tokenization, Part-of-Speech Tagging, Named Entity Recognition, Syntactic & Semantic Dependency Parsing, Document Classification|\n|[Retrieval-based-Voice-Conversion-WebUI](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI)|36.4k|Easily train a good VC model with voice data <= 10 mins!|\n|[Hello-Python](https://github.com/mouredev/Hello-Python)|36.4k|Curso para aprender el lenguaje de programación Python desde cero y para principiantes. 100 clases, 44 horas en vídeo, código, proyectos y grupo de chat. 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Run Ollama models, deploy OpenClaw agents, and manage your entire server stack from one clean web interface.|\n|[Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)|36.1k|Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.|\n|[dspy](https://github.com/stanfordnlp/dspy)|36.1k|DSPy: The framework for programming—not prompting—language models|\n|[mediapipe](https://github.com/google-ai-edge/mediapipe)|36.1k|Cross-platform, customizable ML solutions for live and streaming media.|\n|[CopilotKit](https://github.com/CopilotKit/CopilotKit)|36k|The Frontend Stack for Agents & Generative UI. React, Angular, Mobile, Slack, and more. 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Get started - free.|\n|[Vane](https://github.com/ItzCrazyKns/Vane)|35.7k|Vane is an AI-powered answering engine.|\n|[PDFMathTranslate](https://github.com/PDFMathTranslate/PDFMathTranslate)|35.6k|[EMNLP 2025 Demo] PDF scientific paper translation with preserved formats - 基于 AI 完整保留排版的 PDF 文档全文双语翻译，支持 Google/DeepL/Ollama/OpenAI 等服务，提供 CLI/GUI/MCP/Docker/Zotero|\n|[500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code](https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code)|35.4k|500 AI Machine learning Deep learning Computer vision NLP Projects with code|\n|[detectron2](https://github.com/facebookresearch/detectron2)|34.6k|Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.|\n|[caffe](https://github.com/BVLC/caffe)|34.6k|Caffe: a fast open framework for deep learning.|\n|[C-Plus-Plus](https://github.com/TheAlgorithms/C-Plus-Plus)|34.5k|Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.|\n|[500-AI-Agents-Projects](https://github.com/ashishpatel26/500-AI-Agents-Projects)|34.4k|The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. 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Aims to cover everything from linear regression to deep learning.|\n|[fairseq](https://github.com/facebookresearch/fairseq)|32.2k|Facebook AI Research Sequence-to-Sequence Toolkit written in Python.|\n|[prompt-optimizer](https://github.com/linshenkx/prompt-optimizer)|32.2k|An AI prompt optimizer for writing better prompts and getting better AI results.|\n|[Kronos](https://github.com/shiyu-coder/Kronos)|32.1k|Kronos: A Foundation Model for the Language of Financial Markets|\n|[happy-llm](https://github.com/datawhalechina/happy-llm)|32.1k|📚 从零开始构建大模型|\n|[GPTs](https://github.com/linexjlin/GPTs)|32k|leaked prompts of GPTs|\n|[conductor](https://github.com/conductor-oss/conductor)|32k|Conductor is an event driven agentic workflow engine providing durable and highly resilient execution engine for applications and AI Agents|\n|[self-llm](https://github.com/datawhalechina/self-llm)|31.3k|《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程|\n|[openai-python](https://github.com/openai/openai-python)|31.3k|The official Python library for the OpenAI API|\n|[fish-speech](https://github.com/fishaudio/fish-speech)|31.3k|SOTA Open Source TTS|\n|[pytorch-lightning](https://github.com/Lightning-AI/pytorch-lightning)|31.2k|Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.|\n|[tqdm](https://github.com/tqdm/tqdm)|31.2k|:zap: A Fast, Extensible Progress Bar for Python and CLI|\n|[langfuse](https://github.com/langfuse/langfuse)|31.1k|🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23|\n|[AI-Expert-Roadmap](https://github.com/AMAI-GmbH/AI-Expert-Roadmap)|31.1k|Roadmap to becoming an Artificial Intelligence Expert in 2022|\n|[DeepFaceLive](https://github.com/iperov/DeepFaceLive)|31k|Real-time face swap for PC streaming or video calls|\n|[scientific-agent-skills](https://github.com/K-Dense-AI/scientific-agent-skills)|30.9k|Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.|\n|[onyx](https://github.com/onyx-dot-app/onyx)|30.9k|Open Source AI Platform - AI Chat with advanced features that works with every LLM|\n|[SillyTavern](https://github.com/SillyTavern/SillyTavern)|30.7k|LLM Frontend for Power Users.|\n|[llm.c](https://github.com/karpathy/llm.c)|30.6k|LLM training in simple, raw C/CUDA|\n|[sglang](https://github.com/sgl-project/sglang)|30.3k|SGLang is a high-performance serving framework for large language models and multimodal models.|\n|[stanford_alpaca](https://github.com/tatsu-lab/stanford_alpaca)|30.3k|Code and documentation to train Stanford's Alpaca models, and generate the data.|\n|[tuning_playbook](https://github.com/google-research/tuning_playbook)|30.2k|A playbook for systematically maximizing the performance of deep learning models.|\n|[nanoclaw](https://github.com/nanocoai/nanoclaw)|30.2k|A lightweight alternative to OpenClaw that runs in containers for security. Connects to WhatsApp, Telegram, Slack, Discord, Gmail and other messaging apps,, has memory, scheduled jobs, and runs directly on Anthropic's Agents SDK|\n|[TradingAgents-CN](https://github.com/hsliuping/TradingAgents-CN)|30.2k|基于多智能体LLM的中文金融交易框架 - TradingAgents中文增强版|\n|[storm](https://github.com/stanford-oval/storm)|30.1k|An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.|\n|[AionUi](https://github.com/iOfficeAI/AionUi)|30k|Free, local, open-source 24/7 Cowork app for OpenClaw, Hermes Agent, Claude Code, Codex, OpenCode, Gemini CLI and 20+ more CLI \\| Customize your assistants \\| Star if you like it!|\n|[agents-course](https://github.com/huggingface/agents-course)|30k|This repository contains the Hugging Face Agents Course.|\n|[Jobs_Applier_AI_Agent_AIHawk](https://github.com/feder-cr/Jobs_Applier_AI_Agent_AIHawk)|30k|AIHawk aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in a tailored way.|\n|[applied-ml](https://github.com/eugeneyan/applied-ml)|29.9k|📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.|\n|[EasyOCR](https://github.com/JaidedAI/EasyOCR)|29.8k|Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.|\n|[cli](https://github.com/googleworkspace/cli)|29.7k|Google Workspace CLI — one command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Dynamically built from Google Discovery Service. Includes AI agent skills.|\n|[Mr.-Ranedeer-AI-Tutor](https://github.com/JushBJJ/Mr.-Ranedeer-AI-Tutor)|29.6k|A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.|\n|[signoz](https://github.com/SigNoz/signoz)|29.6k|SigNoz is an open-source, OpenTelemetry-native observability platform for your team and their AI agents. Get logs, metrics, and traces in one tool with features like APM, distributed tracing, log management, infra monitoring, etc. Combined with SigNoz MCP and a native AI teammate (in SigNoz Cloud) it helps you build more resilient apps.|\n|[llmfit](https://github.com/AlexsJones/llmfit)|29.4k|Hundreds of models & providers. One command to find what runs on your hardware.|\n|[llama3](https://github.com/meta-llama/llama3)|29.3k|The official Meta Llama 3 GitHub site|\n|[insightface](https://github.com/deepinsight/insightface)|29.2k|State-of-the-art 2D and 3D Face Analysis Project|\n|[composio](https://github.com/ComposioHQ/composio)|29.2k|Composio powers 1000+ toolkits, tool search, context management, authentication, and a sandboxed workbench to help you build AI agents that turn intent into action.|\n|[data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|29.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.|\n|[nx](https://github.com/nrwl/nx)|29.2k|The Monorepo Platform that amplifies both developers and AI agents. Nx optimizes your builds, scales your CI, and fixes failed PRs automatically. Ship in half the time.|\n|[d2l-en](https://github.com/d2l-ai/d2l-en)|29.2k|Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.|\n|[sim](https://github.com/simstudioai/sim)|29.1k|Build, deploy, and orchestrate AI agents. Sim is the central intelligence layer for your AI workforce.|\n|[FastGPT](https://github.com/labring/FastGPT)|29k|FastGPT is a knowledge-based platform built on the LLMs, offers a comprehensive suite of out-of-the-box capabilities such as data processing, RAG retrieval, and visual AI workflow orchestration, letting you easily develop and deploy complex question-answering systems without the need for extensive setup or configuration.|\n|[void](https://github.com/voideditor/void)|28.8k||\n|[machine-learning-for-software-engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)|28.8k|A complete daily plan for studying to become a machine learning engineer.|\n|[linkedin-skill-assessments-quizzes](https://github.com/Ebazhanov/linkedin-skill-assessments-quizzes)|28.8k|Full reference of LinkedIn answers 2024 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers|\n|[chroma](https://github.com/chroma-core/chroma)|28.8k|Search infrastructure for AI|\n|[graphiti](https://github.com/getzep/graphiti)|28.7k|Build Real-Time Knowledge Graphs for AI Agents|\n|[xgboost](https://github.com/dmlc/xgboost)|28.6k|Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow|\n|[RAG_Techniques](https://github.com/NirDiamant/RAG_Techniques)|28.6k|This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.|\n|[h4cker](https://github.com/The-Art-of-Hacking/h4cker)|28.4k|This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org|\n|[FinceptTerminal](https://github.com/Fincept-Corporation/FinceptTerminal)|28.4k|FinceptTerminal is a modern finance application offering advanced market analytics, investment research, and economic data tools, designed for interactive exploration and data-driven decision-making in a user-friendly environment.|\n|[Scrapegraph-ai](https://github.com/ScrapeGraphAI/Scrapegraph-ai)|28.4k|Python scraper based on AI|\n|[semantic-kernel](https://github.com/microsoft/semantic-kernel)|28.3k|Integrate cutting-edge LLM technology quickly and easily into your apps|\n|[gpt-researcher](https://github.com/assafelovic/gpt-researcher)|28.3k|An autonomous agent that conducts deep research on any data using any LLM providers|\n|[spleeter](https://github.com/deezer/spleeter)|28.3k|Deezer source separation library including pretrained models.|\n|[CloakBrowser](https://github.com/CloakHQ/CloakBrowser)|28.3k|Stealth Chromium that passes every bot detection test. Drop-in Playwright replacement with source-level fingerprint patches. 30/30 tests passed.|\n|[ai-website-cloner-template](https://github.com/JCodesMore/ai-website-cloner-template)|28.3k|Clone any website with one command using AI coding agents|\n|[so-vits-svc](https://github.com/svc-develop-team/so-vits-svc)|28.1k|SoftVC VITS Singing Voice Conversion|\n|[gitleaks](https://github.com/gitleaks/gitleaks)|28.1k|Find secrets with Gitleaks 🔑|\n|[budibase](https://github.com/Budibase/budibase)|28.1k|AI agents, automations and apps that run your operations. Model agnostic.|\n|[fastai](https://github.com/fastai/fastai)|28.1k|The fastai deep learning library|\n|[openai-agents-python](https://github.com/openai/openai-agents-python)|27.9k|A lightweight, powerful framework for multi-agent workflows|\n|[ChatGPT](https://github.com/acheong08/ChatGPT)|27.9k|Reverse engineered ChatGPT API|\n|[cognee](https://github.com/topoteretes/cognee)|27.9k|Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.|\n|[agentscope](https://github.com/agentscope-ai/agentscope)|27.9k|Build and run agents you can see, understand and trust.|\n|[label-studio](https://github.com/HumanSignal/label-studio)|27.8k|Label Studio is a multi-type data labeling and annotation tool with standardized output format|\n|[Resume-Matcher](https://github.com/srbhr/Resume-Matcher)|27.8k|The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.|\n|[InvokeAI](https://github.com/invoke-ai/InvokeAI)|27.6k|Invoke is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, and serves as the foundation for multiple commercial products.|\n|[Hands-On-Large-Language-Models](https://github.com/HandsOnLLM/Hands-On-Large-Language-Models)|27.6k|Official code repo for the O'Reilly Book - \"Hands-On Large Language Models\"|\n|[mlx](https://github.com/ml-explore/mlx)|27.5k|MLX: An array framework for Apple silicon|\n|[cs249r_book](https://github.com/harvard-edge/cs249r_book)|27.5k|Machine Learning Systems|\n|[kestra](https://github.com/kestra-io/kestra)|27.4k|Event Driven Orchestration & Scheduling Platform for Mission Critical Applications|\n|[Qwen3](https://github.com/QwenLM/Qwen3)|27.4k|Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.|\n|[vibe-kanban](https://github.com/BloopAI/vibe-kanban)|27.4k|Get 10X more out of Claude Code, Codex or any coding agent|\n|[generative-models](https://github.com/Stability-AI/generative-models)|27.2k|Generative Models by Stability AI|\n|[opendataloader-pdf](https://github.com/opendataloader-project/opendataloader-pdf)|27.1k|PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.|\n|[repomix](https://github.com/yamadashy/repomix)|27.1k|📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llama, Grok, and more.|\n|[SmsForwarder](https://github.com/pppscn/SmsForwarder)|27.1k|短信转发器——监控Android手机短信、来电、APP通知，并根据指定规则转发到其他手机：钉钉群自定义机器人、钉钉企业内机器人、企业微信群机器人、飞书机器人、企业微信应用消息、邮箱、bark、webhook、Telegram机器人、Server酱、PushPlus、手机短信等。包括主动控制服务端与客户端，让你轻松远程发短信、查短信、查通话、查话簿、查电量等。（V3.0 新增）PS.这个APK主要是学习与自用，如有BUG请提ISSUE，同时欢迎大家提PR指正|\n|[mlflow](https://github.com/mlflow/mlflow)|27k|The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.|\n|[DeepSeek-Reasonix](https://github.com/esengine/DeepSeek-Reasonix)|26.9k|DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.|\n|[timesfm](https://github.com/google-research/timesfm)|26.9k|TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|26.8k|DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.|\n|[OpenViking](https://github.com/volcengine/OpenViking)|26.7k|Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills.|\n|[OpenCLI](https://github.com/jackwener/OpenCLI)|26.6k|Make Any Website into CLI & Use your logged-in browser by AI agent.|\n|[agenticSeek](https://github.com/Fosowl/agenticSeek)|26.6k|Fully Local Manus AI. No APIs, No $200 monthly bills. Enjoy an autonomous agent that thinks, browses the web, and code for the sole cost of electricity. 🔔 Official updates only via twitter @Martin993886460 (Beware of fake account)|\n|[page-agent](https://github.com/alibaba/page-agent)|26.6k|JavaScript in-page GUI agent. Control web interfaces with natural language.|\n|[modular](https://github.com/modular/modular)|26.6k|The Modular Platform (includes MAX & Mojo)|\n|[crush](https://github.com/charmbracelet/crush)|26.6k|Glamourous agentic coding for all 💘|\n|[Handy](https://github.com/cjpais/Handy)|26.5k|A free, open source, and extensible speech-to-text application that works completely offline.|\n|[darknet](https://github.com/pjreddie/darknet)|26.5k|Convolutional Neural Networks|\n|[Detectron](https://github.com/facebookresearch/Detectron)|26.4k|FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.|\n|[deep-learning-for-image-processing](https://github.com/WZMIAOMIAO/deep-learning-for-image-processing)|26.3k|deep learning for image processing including classification and object-detection etc.|\n|[heretic](https://github.com/p-e-w/heretic)|26.3k|Fully automatic censorship removal for language models|\n|[kilocode](https://github.com/Kilo-Org/kilocode)|26.2k|Kilo is the all-in-one agentic engineering platform. Build, ship, and iterate faster with the most popular open source coding agent.|\n|[mastra](https://github.com/mastra-ai/mastra)|26.2k|Mastra is the modern TypeScript framework for AI-powered applications and agents.|\n|[pumpkin-book](https://github.com/datawhalechina/pumpkin-book)|25.9k|南瓜书：《机器学习》（西瓜书）公式详解|\n|[DeepTutor](https://github.com/HKUDS/DeepTutor)|25.9k|DeepTutor: Lifelong Personalized Tutoring. https://deeptutor.info/.|\n|[haystack](https://github.com/deepset-ai/haystack)|25.9k|Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.|\n|[Chat2DB](https://github.com/OtterMind/Chat2DB)|25.9k|AI-driven database tool and SQL client, The hottest GUI client, supporting MySQL, Oracle, PostgreSQL, DB2, SQL Server, DB2, SQLite, H2, ClickHouse, and more.|\n|[flux](https://github.com/black-forest-labs/flux)|25.7k|Official inference repo for FLUX.1 models|\n|[MiniGPT-4](https://github.com/Vision-CAIR/MiniGPT-4)|25.7k|Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)|\n|[shap](https://github.com/shap/shap)|25.6k|A game theoretic approach to explain the output of any machine learning model.|\n|[handson-ml](https://github.com/ageron/handson-ml)|25.6k|⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|25.6k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[Anthropic-Cybersecurity-Skills](https://github.com/mukul975/Anthropic-Cybersecurity-Skills)|25.6k|817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0|\n|[ai](https://github.com/vercel/ai)|25.6k|The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents|\n|[kotaemon](https://github.com/Cinnamon/kotaemon)|25.5k|An open-source RAG-based tool for chatting with your documents.|\n|[chatterbox](https://github.com/resemble-ai/chatterbox)|25.5k|SoTA open-source TTS|\n|[Pixelle-Video](https://github.com/ATH-MaaS/Pixelle-Video)|25.4k|🚀 AI 全自动短视频引擎 \\| AI Fully Automated Short Video Engine|\n|[vit-pytorch](https://github.com/lucidrains/vit-pytorch)|25.4k|Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch|\n|[llamafile](https://github.com/mozilla-ai/llamafile)|25.4k|Distribute and run LLMs with a single file.|\n|[ultimatevocalremovergui](https://github.com/Anjok07/ultimatevocalremovergui)|25.4k|GUI for a Vocal Remover that uses Deep Neural Networks.|\n|[planning-with-files](https://github.com/OthmanAdi/planning-with-files)|25.4k|Persistent file-based planning for AI coding agents and long-running agentic tasks. Crash-proof markdown plans that survive context loss and /clear, plus a deterministic completion gate and multi-agent shared state on disk. Manus-style. Works with Claude Code, Codex CLI, Cursor, Kiro, OpenCode and 60+ agents via the SKILL.md standard.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|25.2k|Image-to-Image Translation in PyTorch|\n|[WaveFunctionCollapse](https://github.com/mxgmn/WaveFunctionCollapse)|25.2k|Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics|\n|[fastbook](https://github.com/fastai/fastbook)|25.1k|The fastai book, published as Jupyter Notebooks|\n|[labelImg](https://github.com/HumanSignal/labelImg)|25k|LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.|\n|[JARVIS](https://github.com/microsoft/JARVIS)|25k|JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf|\n|[gpt-2](https://github.com/openai/gpt-2)|25k|Code for the paper \"Language Models are Unsupervised Multitask Learners\"|\n|[nextai-translator](https://github.com/nextai-translator/nextai-translator)|24.9k|基于 ChatGPT API 的划词翻译浏览器插件和跨平台桌面端应用 - Browser extension and cross-platform desktop application for translation based on ChatGPT API.|\n|[LLaVA](https://github.com/haotian-liu/LLaVA)|24.9k|[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.|\n|[PlotNeuralNet](https://github.com/HarisIqbal88/PlotNeuralNet)|24.9k|Latex code for making neural networks diagrams|\n|[toon](https://github.com/toon-format/toon)|24.9k|🎒 Token-Oriented Object Notation (TOON) – Compact, human-readable, schema-aware JSON for LLM prompts. Spec, benchmarks, TypeScript SDK.|\n|[A2A](https://github.com/a2aproject/A2A)|24.8k|Agent2Agent (A2A) is an open protocol enabling communication and interoperability between opaque agentic applications.|\n|[llm-action](https://github.com/liguodongiot/llm-action)|24.7k|本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）|\n|[crawlee](https://github.com/apify/crawlee)|24.7k|Crawlee—A web scraping and browser automation library for Node.js to build reliable crawlers. In JavaScript and TypeScript. Extract data for AI, LLMs, RAG, or GPTs. Download HTML, PDF, JPG, PNG, and other files from websites. Works with Puppeteer, Playwright, Cheerio, JSDOM, and raw HTTP. Both headful and headless mode. 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Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).|\n|[DeepResearch](https://github.com/Alibaba-NLP/DeepResearch)|19.7k|Tongyi Deep Research, the Leading Open-source Deep Research Agent|\n|[Qwen3-VL](https://github.com/QwenLM/Qwen3-VL)|19.6k|Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.|\n|[ml-agents](https://github.com/Unity-Technologies/ml-agents)|19.6k|The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.|\n|[sam2](https://github.com/facebookresearch/sam2)|19.5k|The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.|\n|[ebook2audiobook](https://github.com/DrewThomasson/ebook2audiobook)|19.5k|Generate audiobooks from e-books, voice cloning & 1158+ languages!|\n|[code-review-graph](https://github.com/tirth8205/code-review-graph)|19.5k|Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.|\n|[DB-GPT](https://github.com/eosphoros-ai/DB-GPT)|19.5k|open-source agentic AI data assistant for the next generation of AI + Data products.|\n|[Dive-into-DL-PyTorch](https://github.com/ShusenTang/Dive-into-DL-PyTorch)|19.4k|本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。|\n|[deep-research](https://github.com/dzhng/deep-research)|19.4k|An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models. 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Run any coding agent with your own subscription. Available on desktop and mobile.|\n|[nndl](https://github.com/nndl/nndl)|19k|邱锡鹏《神经网络与深度学习》（蒲公英书）理论书 v2 与通识版|\n|[Chinese-LLaMA-Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca)|18.9k|中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)|\n|[evals](https://github.com/openai/evals)|18.9k|Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.|\n|[alpaca-lora](https://github.com/tloen/alpaca-lora)|18.9k|Instruct-tune LLaMA on consumer hardware|\n|[sentence-transformers](https://github.com/huggingface/sentence-transformers)|18.9k|State-of-the-Art Embeddings, Retrieval, and Reranking|\n|[kirara-ai](https://github.com/lss233/kirara-ai)|18.9k|🤖 可 DIY 的 多模态 AI 聊天机器人 \\| 🚀 快速接入 微信、 QQ、Telegram、等聊天平台 \\| 🦈支持DeepSeek、Grok、Claude、Ollama、Gemini、OpenAI \\| 工作流系统、网页搜索、AI画图、人设调教、虚拟女仆、语音对话 \\||\n|[trl](https://github.com/huggingface/trl)|18.8k|Train transformer language models with reinforcement learning.|\n|[LivePortrait](https://github.com/KlingAIResearch/LivePortrait)|18.7k|Bring portraits to life!|\n|[eliza](https://github.com/elizaOS/eliza)|18.7k|Open source agentic operating system|\n|[LightGBM](https://github.com/lightgbm-org/LightGBM)|18.6k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.|\n|[ds4](https://github.com/antirez/ds4)|18.5k|DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm|\n|[pydantic-ai](https://github.com/pydantic/pydantic-ai)|18.5k|AI Agent Framework, the Pydantic way|\n|[DeOldify](https://github.com/jantic/DeOldify)|18.5k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[screenity](https://github.com/alyssaxuu/screenity)|18.4k|The free and privacy-friendly screen recorder with no limits 🎥|\n|[ml-engineering](https://github.com/stas00/ml-engineering)|18.4k|Machine Learning Engineering Open Book|\n|[llama-cookbook](https://github.com/meta-llama/llama-cookbook)|18.4k|Welcome to the Llama Cookbook! 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We also show you how to solve end to end problems using Llama model family and using them on various provider services|\n|[pytorch-deep-learning](https://github.com/mrdbourke/pytorch-deep-learning)|18.4k|Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.|\n|[web-llm](https://github.com/mlc-ai/web-llm)|18.4k|High-performance In-browser LLM Inference Engine|\n|[hindsight](https://github.com/vectorize-io/hindsight)|18.3k|Hindsight: Agent Memory That Learns|\n|[pyvideotrans](https://github.com/jianchang512/pyvideotrans)|18.3k|Translate the video from one language to another and embed dubbing & subtitles.|\n|[AirSim](https://github.com/microsoft/AirSim)|18.3k|Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research|\n|[WeKnora](https://github.com/Tencent/WeKnora)|18.3k|Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.|\n|[easy-vibe](https://github.com/datawhalechina/easy-vibe)|18.2k|💻 vibe coding 2026 \\| Your First Modern Coding course beginners to master step by step.|\n|[parlant](https://github.com/emcie-co/parlant)|18.2k|Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.|\n|[keploy](https://github.com/keploy/keploy)|18.1k|Open-source platform for creating safe, isolated production sandboxes for API, integration, and E2E testing.|\n|[agentic](https://github.com/transitive-bullshit/agentic)|18.1k|Your API ⇒ Paid MCP. 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Finding the Scaling Law of Agents. https://www.camel-ai.org|\n|[leon](https://github.com/leon-ai/leon)|17.4k|🧠 Leon is your open-source personal assistant.|\n|[ml-visuals](https://github.com/dair-ai/ml-visuals)|17.3k|🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.|\n|[ML-YouTube-Courses](https://github.com/dair-ai/ML-YouTube-Courses)|17.3k|📺 Discover the latest machine learning / AI courses on YouTube.|\n|[agency-agents-zh](https://github.com/jnMetaCode/agency-agents-zh)|17.3k|🎭 266 个即插即用的 AI 专家角色 — 支持 Hermes Agent/Claude Code/Cursor/Copilot 等 18 种工具，覆盖工程/设计/营销/金融等 20 个部门。含 50 个中国市场原创智能体（小红书/抖音/微信/飞书/钉钉等）。搭配编排器 agency-orchestrator，一句话即可让多位专家按 DAG 自动协作。|\n|[deepwiki-open](https://github.com/AsyncFuncAI/deepwiki-open)|17.3k|Open Source DeepWiki: AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories. Join the discord: https://discord.gg/gMwThUMeme|\n|[OmniRoute](https://github.com/diegosouzapw/OmniRoute)|17.3k|Never stop coding. Free AI gateway: one endpoint, 231+ providers (50+ free), connect Claude Code, Codex, Cursor, Cline & Copilot to FREE Claude/GPT/Gemini. RTK+Caveman stacked compression saves 15-95% tokens, smart auto-fallback, MCP/A2A, multimodal APIs, Desktop/PWA.|\n|[magika](https://github.com/google/magika)|17.2k|Fast and accurate AI powered file content types detection|\n|[ai-guide](https://github.com/liyupi/ai-guide)|17.2k|程序员鱼皮的 AI 资源大全 + Vibe Coding 零基础教程，分享 OpenClaw 保姆级教程、大模型玩法（DeepSeek / GPT / Gemini / Claude / GLM）、最新 AI 资讯、Prompt 提示词大全、AI 知识百科（Agent Skills / RAG / MCP / A2A）、AI 编程教程（Harness Engineering）、AI 工具用法（Cursor / Claude Code / TRAE / Codex / Copilot）、AI 开发框架教程（Spring AI / LangChain）、AI 产品变现指南，帮你快速掌握 AI 技术，走在时代前沿。本项目为开源文档 aiguide，已升级为鱼皮 AI 导航网站|\n|[generative-ai](https://github.com/GoogleCloudPlatform/generative-ai)|17.2k|Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform|\n|[carrot](https://github.com/xx025/carrot)|17.1k|AI 工具导航大全，帮你快速筛选免费、实用、高效的网站资源|\n|[Megatron-LM](https://github.com/NVIDIA/Megatron-LM)|17.1k|Ongoing research training transformer models at scale|\n|[Book-Mathematical-Foundation-of-Reinforcement-Learning](https://github.com/MathFoundationRL/Book-Mathematical-Foundation-of-Reinforcement-Learning)|17k|This is the homepage of a new book entitled \"Mathematical Foundations of Reinforcement Learning.\"|\n|[kubesphere](https://github.com/kubesphere/kubesphere)|17k|The container platform tailored for Kubernetes multi-cloud, datacenter, and edge management ⎈ 🖥 ☁️|\n|[LangBot](https://github.com/langbot-app/LangBot)|16.9k|Production-grade platform for building agentic IM bots - 生产级多平台智能机器人开发平台/ Agent、知识库编排、插件系统 / Bots for Discord / Slack / LINE / Telegram / WeChat(企业微信, 企微智能机器人, 公众号) / 飞书 / 钉钉 / QQ / Matrix e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow, Coze, Claude, Gemini, GLM, Ollama, SiliconFlow, Moonshot, openclaw / hermes agent, deerflow|\n|[deepeval](https://github.com/confident-ai/deepeval)|16.8k|The LLM Evaluation Framework|\n|[argo-workflows](https://github.com/argoproj/argo-workflows)|16.8k|Workflow Engine for Kubernetes|\n|[GNNPapers](https://github.com/thunlp/GNNPapers)|16.8k|Must-read papers on graph neural networks (GNN)|\n|[baselines](https://github.com/openai/baselines)|16.7k|OpenAI Baselines: high-quality implementations of reinforcement learning algorithms|\n|[micrograd](https://github.com/karpathy/micrograd)|16.7k|A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API|\n|[Qwen3-Coder](https://github.com/QwenLM/Qwen3-Coder)|16.7k|Qwen3-Coder is the code version of Qwen3, the large language model series developed by Qwen team.|\n|[leedl-tutorial](https://github.com/datawhalechina/leedl-tutorial)|16.7k|《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases|\n|[Wan2.2](https://github.com/Wan-Video/Wan2.2)|16.7k|Wan: Open and Advanced Large-Scale Video Generative Models|\n|[OfficeCLI](https://github.com/iOfficeAI/OfficeCLI)|16.6k|OfficeCLI is the first and best Office suite purpose-built for AI agents to read, edit, and automate Word, Excel, and PowerPoint files. Free, open-source, single binary, no Office installation required.|\n|[weaviate](https://github.com/weaviate/weaviate)|16.6k|Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.|\n|[ai-pdf-chatbot-langchain](https://github.com/mayooear/ai-pdf-chatbot-langchain)|16.6k|AI PDF chatbot agent built with LangChain & LangGraph|\n|[Wan2.1](https://github.com/Wan-Video/Wan2.1)|16.6k|Wan: Open and Advanced Large-Scale Video Generative Models|\n|[LaTeX-OCR](https://github.com/lukas-blecher/LaTeX-OCR)|16.5k|pix2tex: Using a ViT to convert images of equations into LaTeX code.|\n|[Screenshot-to-code](https://github.com/emilwallner/Screenshot-to-code)|16.5k|A neural network that transforms a design mock-up into a static website.|\n|[Foundations-of-LLMs](https://github.com/ZJU-LLMs/Foundations-of-LLMs)|16.5k|A book for Learning the Foundations of LLMs|\n|[rowboat](https://github.com/rowboatlabs/rowboat)|16.5k|Open-source AI coworker, with memory|\n|[gensim](https://github.com/piskvorky/gensim)|16.5k|Topic Modelling for Humans|\n|[ChatALL](https://github.com/ai-shifu/ChatALL)|16.4k|Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vicuna, Claude, ChatGLM, MOSS, 讯飞星火, 文心一言 and more, discover the best answers|\n|[herdr](https://github.com/ogulcancelik/herdr)|16.4k|agent multiplexer that lives in your terminal.|\n|[novel](https://github.com/steven-tey/novel)|16.4k|Notion-style WYSIWYG editor with AI-powered autocompletion.|\n|[numpy-ml](https://github.com/ddbourgin/numpy-ml)|16.3k|Machine learning, in numpy|\n|[codellama](https://github.com/meta-llama/codellama)|16.3k|Inference code for CodeLlama models|\n|[cvat](https://github.com/cvat-ai/cvat)|16.3k|Computer Vision Annotation Tool (CVAT) is a leading platform for building high-quality visual datasets for vision AI. It offers open-source, cloud, and enterprise products, as well as labeling services, for image, video, and 3D annotation with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.|\n|[TensorFlow-Course](https://github.com/instillai/TensorFlow-Course)|16.3k|:satellite: Simple and ready-to-use tutorials for TensorFlow|\n|[edict](https://github.com/cft0808/edict)|16.2k|🏛️ 三省六部制 · OpenClaw Multi-Agent Orchestration System — 9 specialized AI agents with real-time dashboard, model config, and full audit trails|\n|[web-ui](https://github.com/browser-use/web-ui)|16.2k|🖥️ Run AI Agent in your browser.|\n|[transformers.js](https://github.com/huggingface/transformers.js)|16.2k|State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!|\n|[RagaAI-Catalyst](https://github.com/raga-ai-hub/RagaAI-Catalyst)|16.1k|Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view|\n|[freellmapi](https://github.com/tashfeenahmed/freellmapi)|16.1k|OpenAI-compatible proxy that stacks the free tiers of 16 LLM providers (~1.7B tokens/month) behind one /v1 endpoint — plus any custom OpenAI-compatible endpoint. Smart routing, automatic failover, encrypted keys. Personal experimentation only.|\n|[labelme](https://github.com/wkentaro/labelme)|16k|Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.|\n|[hermes-webui](https://github.com/nesquena/hermes-webui)|16k|Hermes WebUI: The best way to use Hermes Agent from the web or from your phone!|\n|[Swin-Transformer](https://github.com/microsoft/Swin-Transformer)|16k|This is an official implementation for \"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows\".|\n|[browser-harness](https://github.com/browser-use/browser-harness)|16k|Browser Harness \\| Self-healing harness that enables LLMs to complete any task.|\n|[mcp-toolbox](https://github.com/googleapis/mcp-toolbox)|16k|MCP Toolbox for Databases is an open source MCP server for databases.|\n|[stable-diffusion-webui-colab](https://github.com/camenduru/stable-diffusion-webui-colab)|15.9k|stable diffusion webui colab|\n|[lectures](https://github.com/oxford-cs-deepnlp-2017/lectures)|15.9k|Oxford Deep NLP 2017 course|\n|[dagster](https://github.com/dagster-io/dagster)|15.8k|An orchestration platform for the development, production, and observation of data assets.|\n|[WrenAI](https://github.com/Canner/WrenAI)|15.8k|GenBI (Generative BI) for AI agents, an open-source, governed text-to-SQL through an open context layer that turns natural-language questions into trusted dashboards, charts, and SQL across 20+ data sources, such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Amazon Redshift, Databricks and more.|\n|[kubeflow](https://github.com/kubeflow/kubeflow)|15.8k|Machine Learning Toolkit for Kubernetes|\n|[memvid](https://github.com/memvid/memvid)|15.8k|Memory layer for AI Agents. 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Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages|\n|[instructor](https://github.com/567-labs/instructor)|13.5k|structured outputs for llms|\n|[litgpt](https://github.com/Lightning-AI/litgpt)|13.5k|20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.|\n|[llm-universe](https://github.com/datawhalechina/llm-universe)|13.5k|本项目是一个面向小白开发者的大模型应用开发教程，在线阅读地址：https://datawhalechina.github.io/llm-universe/|\n|[opencode](https://github.com/opencode-ai/opencode)|13.5k|A powerful AI coding agent. Built for the terminal.|\n|[nanobrowser](https://github.com/nanobrowser/nanobrowser)|13.5k|Open-Source Chrome extension for AI-powered web automation. Run multi-agent workflows using your own LLM API key. 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No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.|\n|[hermes-desktop](https://github.com/fathah/hermes-desktop)|13.3k|Desktop Companion for Hermes Agent|\n|[lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)|13.3k|A framework for few-shot evaluation of language models.|\n|[Deep-Learning-with-TensorFlow-book](https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book)|13.2k|深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.|\n|[waoowaoo](https://github.com/waooAI/waoowaoo)|13.2k|首家工业级全流程 AI 影视生产平台。Industry-first professional AI Agent platform for controllable film & video production. From shorts to live-action with Hollywood-standard workflows.|\n|[Halfrost-Field](https://github.com/halfrost/Halfrost-Field)|13.2k|✍🏻 Source Code Deep Dives, System Design & Engineering Blogs \\| Halfrost-Field 冰霜之地：源码解析、系统设计与工程实践笔记|\n|[nmap](https://github.com/nmap/nmap)|13.2k|Nmap - the Network Mapper. Github mirror of official SVN repository.|\n|[SkillSpector](https://github.com/NVIDIA/SkillSpector)|13.2k|Security scanner for AI agent skills. Detect vulnerabilities, malicious patterns, and security risks.|\n|[TensorRT](https://github.com/NVIDIA/TensorRT)|13.2k|NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.|\n|[ai-berkshire](https://github.com/xbtlin/ai-berkshire)|13.1k|AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。\\| AI-era Berkshire: a value investing research framework built for Claude Code / Codex. 4 masters' methodologies + multi-agent adversarial analysis.|\n|[Ai-Learn](https://github.com/tangyudi/Ai-Learn)|13.1k|人工智能学习路线图，整理近200个实战案例与项目，免费提供配套教材，零基础入门，就业实战！包括：Python，数学，机器学习，数据分析，深度学习，计算机视觉，自然语言处理，PyTorch tensorflow machine-learning,deep-learning data-analysis data-mining mathematics data-science artificial-intelligence python tensorflow tensorflow2 caffe keras pytorch algorithm numpy pandas matplotlib seaborn nlp cv等热门领域|\n|[dinov2](https://github.com/facebookresearch/dinov2)|13.1k|PyTorch code and models for the DINOv2 self-supervised learning method.|\n|[chatgpt-google-extension](https://github.com/wong2/chatgpt-google-extension)|13.1k|This project is deprecated. Check my new project ChatHub:|\n|[supertonic](https://github.com/supertone-inc/supertonic)|13.1k|Lightning-Fast, On-Device, Multilingual TTS — running natively via ONNX.|\n|[md](https://github.com/doocs/md)|13k|✍ WeChat Markdown Editor \\| 一款高度简洁的微信 Markdown 编辑器：支持 Markdown 语法、自定义主题样式、内容管理、多图床、AI 助手等特性|\n|[PaddleFormers](https://github.com/PaddlePaddle/PaddleFormers)|13k|PaddleFormers is an easy-to-use library of pre-trained large language model zoo based on PaddlePaddle.|\n|[E2B](https://github.com/e2b-dev/E2B)|13k|Open-source, secure environment with real-world tools for enterprise-grade agents.|\n|[tutorials](https://github.com/MorvanZhou/tutorials)|13k|机器学习相关教程|\n|[playground](https://github.com/tensorflow/playground)|13k|Play with neural networks!|\n|[PaddleNLP](https://github.com/PaddlePaddle/PaddleNLP)|13k|Easy-to-use and powerful LLM and SLM library with awesome model zoo.|\n|[gorilla](https://github.com/ShishirPatil/gorilla)|12.9k|Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)|\n|[dalai](https://github.com/cocktailpeanut/dalai)|12.9k|The simplest way to run LLaMA on your local machine|\n|[pytorch-grad-cam](https://github.com/jacobgil/pytorch-grad-cam)|12.9k|Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.|\n|[CogVideo](https://github.com/zai-org/CogVideo)|12.9k|text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)|\n|[CycleGAN](https://github.com/junyanz/CycleGAN)|12.9k|Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.|\n|[deep-learning-drizzle](https://github.com/kmario23/deep-learning-drizzle)|12.9k|Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!|\n|[pytorch-book](https://github.com/chenyuntc/pytorch-book)|12.8k|PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation (《深度学习框架PyTorch：入门与实战》)|\n|[stable-diffusion-webui-forge](https://github.com/lllyasviel/stable-diffusion-webui-forge)|12.8k||\n|[Meshroom](https://github.com/alicevision/Meshroom)|12.8k|Node-based Visual Programming Toolbox|\n|[dio](https://github.com/cfug/dio)|12.8k|A powerful HTTP client for Dart and Flutter, which supports global settings, Interceptors, FormData, aborting and canceling a request, files uploading and downloading, requests timeout, custom adapters, etc.|\n|[clip-as-service](https://github.com/jina-ai/clip-as-service)|12.8k|🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP|\n|[fashion-mnist](https://github.com/zalandoresearch/fashion-mnist)|12.8k|A MNIST-like fashion product database. Benchmark :point_down:|\n|[machine-learning-interview](https://github.com/khangich/machine-learning-interview)|12.7k|Machine Learning Interviews from FAANG, Snapchat, LinkedIn. I have offers from Snapchat, Coupang, Stitchfix etc. Blog: mlengineer.io.|\n|[txtai](https://github.com/neuml/txtai)|12.7k|💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows|\n|[SkillOpt](https://github.com/microsoft/SkillOpt)|12.7k|SkillOpt is a text-space optimizer that trains reusable natural-language skills for frozen LLM agents through trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts.|\n|[DiffSynth-Studio](https://github.com/modelscope/DiffSynth-Studio)|12.7k|Enjoy the magic of Diffusion models!|\n|[turbovec](https://github.com/RyanCodrai/turbovec)|12.7k|A vector index built on TurboQuant, written in Rust with Python bindings|\n|[LEANN](https://github.com/StarTrail-org/LEANN)|12.7k|[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.|\n|[AI-Papers-of-the-Week](https://github.com/dair-ai/AI-Papers-of-the-Week)|12.6k|🔥Highlighting the top ML papers every week.|\n|[PaddleSpeech](https://github.com/PaddlePaddle/PaddleSpeech)|12.6k|Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.|\n|[vision_transformer](https://github.com/google-research/vision_transformer)|12.6k||\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|12.6k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[Time-Series-Library](https://github.com/thuml/Time-Series-Library)|12.6k|A Library for Advanced Deep Time Series Models for General Time Series Analysis.|\n|[langchain4j](https://github.com/langchain4j/langchain4j)|12.6k|LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.|\n|[HRM](https://github.com/sapientinc/HRM)|12.6k|Hierarchical Reasoning Model Official Release|\n|[nsfw_data_scraper](https://github.com/alex000kim/nsfw_data_scraper)|12.6k|Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier|\n|[Open-LLM-VTuber](https://github.com/Open-LLM-VTuber/Open-LLM-VTuber)|12.6k|Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms|\n|[predictionio](https://github.com/apache/predictionio)|12.5k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[mi-gpt](https://github.com/idootop/mi-gpt)|12.5k|🏠 将小爱音箱接入 ChatGPT 和豆包，改造成你的专属语音助手。|\n|[CVPR2024-Paper-Code-Interpretation](https://github.com/extreme-assistant/CVPR2024-Paper-Code-Interpretation)|12.5k|cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理|\n|[unity-mcp](https://github.com/CoplayDev/unity-mcp)|12.5k|Unity MCP acts as a bridge between AI assistants and your Unity Editor. Give your LLM tools to manage assets, control scenes, edit scripts, and automate tasks within Unity.|\n|[PocketFlow-Tutorial-Codebase-Knowledge](https://github.com/The-Pocket/PocketFlow-Tutorial-Codebase-Knowledge)|12.4k|Pocket Flow: Codebase to Tutorial|\n|[gateway](https://github.com/Portkey-AI/gateway)|12.4k|A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.|\n|[superset](https://github.com/superset-sh/superset)|12.4k|Code Editor for the AI Agents Era - Run an army of Claude Code, Codex, etc. on your machine|\n|[Qwen3-TTS](https://github.com/QwenLM/Qwen3-TTS)|12.4k|Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.|\n|[OpenLLM](https://github.com/bentoml/OpenLLM)|12.4k|Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.|\n|[tensorflow-zh](https://github.com/jikexueyuanwiki/tensorflow-zh)|12.4k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[LunaTranslator](https://github.com/HIllya51/LunaTranslator)|12.4k|视觉小说翻译器 / Visual Novel Translator|\n|[LangGPT](https://github.com/langgptai/LangGPT)|12.3k|LangGPT: Empowering everyone to become a prompt expert! 🚀 📌 结构化提示词（Structured Prompt）提出者 📌 元提示词（Meta-Prompt）发起者 📌 最流行的提示词落地范式 \\| Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ \\| Battle-tested by thousands of users worldwide Created by 云中江树|\n|[HunyuanVideo](https://github.com/Tencent-Hunyuan/HunyuanVideo)|12.3k|HunyuanVideo: A Systematic Framework For Large Video Generation Model|\n|[RemoveWindowsAI](https://github.com/zoicware/RemoveWindowsAI)|12.3k|Force Remove Copilot, Recall and More in Windows 11|\n|[chineseocr_lite](https://github.com/DayBreak-u/chineseocr_lite)|12.3k|超轻量级中文ocr，支持竖排文字识别, 支持ncnn、mnn、tnn推理 ( dbnet(1.8M) + crnn(2.5M) + anglenet(378KB)) 总模型仅4.7M|\n|[GPU-Puzzles](https://github.com/srush/GPU-Puzzles)|12.3k|Solve puzzles. Learn CUDA.|\n|[chainlit](https://github.com/Chainlit/chainlit)|12.3k|Build Conversational AI in minutes ⚡️|\n|[eino](https://github.com/cloudwego/eino)|12.3k|The ultimate LLM/AI application development framework in Go.|\n|[note-gen](https://github.com/codexu/note-gen)|12.3k|A cross-platform Markdown AI note-taking software.|\n|[MidJourney-Styles-and-Keywords-Reference](https://github.com/willwulfken/MidJourney-Styles-and-Keywords-Reference)|12.3k|A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!|\n|[InsForge](https://github.com/InsForge/InsForge)|12.3k|The all-in-one, open-source backend platform for agentic coding. InsForge gives your coding agent database, auth, storage, compute, hosting, and AI gateway to ship full-stack apps end-to-end.|\n|[zerox](https://github.com/getomni-ai/zerox)|12.2k|OCR & Document Extraction using vision models|\n|[Chinese-Word-Vectors](https://github.com/Embedding/Chinese-Word-Vectors)|12.2k|100+ Chinese Word Vectors 上百种预训练中文词向量|\n|[ChatGPT_DAN](https://github.com/0xk1h0/ChatGPT_DAN)|12.2k|ChatGPT DAN, Jailbreaks prompt|\n|[axolotl](https://github.com/axolotl-ai-cloud/axolotl)|12.2k|Go ahead and axolotl questions|\n|[colmap](https://github.com/colmap/colmap)|12.2k|COLMAP - Structure-from-Motion and Multi-View Stereo|\n|[llm](https://github.com/simonw/llm)|12.2k|Access large language models from the command-line|\n|[LLMSurvey](https://github.com/RUCAIBox/LLMSurvey)|12.2k|The official GitHub page for the survey paper \"A Survey of Large Language Models\".|\n|[shell_gpt](https://github.com/TheR1D/shell_gpt)|12.2k|A command-line productivity tool powered by AI large language models like GPT-5, will help you accomplish your tasks faster and more efficiently.|\n|[External-Attention-pytorch](https://github.com/xmu-xiaoma666/External-Attention-pytorch)|12.2k|🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐|\n|[Gymnasium](https://github.com/Farama-Foundation/Gymnasium)|12.2k|A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)|\n|[MOSS](https://github.com/OpenMOSS/MOSS)|12.2k|An open-source tool-augmented conversational language model from Fudan University|\n|[lime](https://github.com/marcotcr/lime)|12.2k|Lime: Explaining the predictions of any machine learning classifier|\n|[ubicloud](https://github.com/ubicloud/ubicloud)|12.1k|Open source alternative to AWS. Elastic compute, block storage (non replicated), firewall and load balancer, managed Postgres, K8s, AI inference, and IAM services.|\n|[compromise](https://github.com/spencermountain/compromise)|12.1k|modest natural-language processing|\n|[claude-context](https://github.com/zilliztech/claude-context)|12.1k|Code search MCP for Claude Code. Make entire codebase the context for any coding agent.|\n|[agent-framework](https://github.com/microsoft/agent-framework)|12.1k|A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.|\n|[pr-agent](https://github.com/The-PR-Agent/pr-agent)|12.1k|🚀 PR Agent: The Original Open-Source PR Reviewer. This project It is not the Qodo free tier.|\n|[char-rnn](https://github.com/karpathy/char-rnn)|12.1k|Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch|\n|[MiMo-Code](https://github.com/XiaomiMiMo/MiMo-Code)|12.1k|MiMo Code: Where Models and Agents Co-Evolve|\n|[BrowserOS](https://github.com/browseros-ai/BrowserOS)|12.1k|🌐 The open-source Agentic browser; alternative to ChatGPT Atlas, Perplexity Comet, Dia.|\n|[pix2code](https://github.com/tonybeltramelli/pix2code)|12k|pix2code: Generating Code from a Graphical User Interface Screenshot|\n|[Agent-S](https://github.com/simular-ai/Agent-S)|12k|Agent S: an open agentic framework that uses computers like a human|\n|[OpenSandbox](https://github.com/opensandbox-group/OpenSandbox)|12k|Secure, Fast, and Extensible Sandbox runtime for AI agents.|\n|[kubeshark](https://github.com/kubeshark/kubeshark)|12k|eBPF-powered network observability for Kubernetes. Indexes L4/L7 traffic with full K8s context, decrypts TLS without keys. Queryable by AI agents via MCP and humans via dashboard.|\n|[h2ogpt](https://github.com/h2oai/h2ogpt)|12k|Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/|\n|[sentencepiece](https://github.com/google/sentencepiece)|12k|Unsupervised text tokenizer for Neural Network-based text generation.|\n|[ui](https://github.com/creativetimofficial/ui)|12k|Open-source components, blocks, and AI agents designed to speed up your workflow. Import them seamlessly into your favorite tools through Registry and MCPs.|\n|[fastapi_mcp](https://github.com/tadata-org/fastapi_mcp)|11.9k|Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!|\n|[FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding)|11.9k|Retrieval and Retrieval-augmented LLMs|\n|[allennlp](https://github.com/allenai/allennlp)|11.9k|An open-source NLP research library, built on PyTorch.|\n|[neural-enhance](https://github.com/alexjc/neural-enhance)|11.9k|Super Resolution for images using deep learning.|\n|[spinningup](https://github.com/openai/spinningup)|11.9k|An educational resource to help anyone learn deep reinforcement learning.|\n|[trae-agent](https://github.com/bytedance/trae-agent)|11.8k|Trae Agent is an LLM-based agent for general purpose software engineering tasks.|\n|[seamless_communication](https://github.com/facebookresearch/seamless_communication)|11.8k|Foundational Models for State-of-the-Art Speech and Text Translation|\n|[nerfstudio](https://github.com/nerfstudio-project/nerfstudio)|11.8k|A collaboration friendly studio for NeRFs|\n|[ludwig](https://github.com/ludwig-ai/ludwig)|11.7k|Low-code framework for building custom LLMs, neural networks, and other AI models|\n|[tensorzero](https://github.com/tensorzero/tensorzero)|11.7k|TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.|\n|[speechbrain](https://github.com/speechbrain/speechbrain)|11.7k|A PyTorch-based Speech Toolkit|\n|[Transformers-Tutorials](https://github.com/NielsRogge/Transformers-Tutorials)|11.7k|This repository contains demos I made with the Transformers library by HuggingFace.|\n|[segmentation_models.pytorch](https://github.com/qubvel-org/segmentation_models.pytorch)|11.7k|Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.|\n|[great_expectations](https://github.com/fivetran/great_expectations)|11.6k|Always know what to expect from your data.|\n|[inbox-zero](https://github.com/elie222/inbox-zero)|11.6k|The world's best AI personal assistant for email. Open source app to help you reach inbox zero fast.|\n|[PythonPark](https://github.com/Jack-Cherish/PythonPark)|11.6k|Python 开源项目之「自学编程之路」，保姆级教程：AI实验室、宝藏视频、数据结构、学习指南、机器学习实战、深度学习实战、网络爬虫、大厂面经、程序人生、资源分享。|\n|[cleanlab](https://github.com/cleanlab/cleanlab)|11.6k|Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.|\n|[reader](https://github.com/jina-ai/reader)|11.5k|Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/|\n|[LeetCUDA](https://github.com/xlite-dev/LeetCUDA)|11.5k|📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉|\n|[Pytorch-UNet](https://github.com/milesial/Pytorch-UNet)|11.5k|PyTorch implementation of the U-Net for image semantic segmentation with high quality images|\n|[liteparse](https://github.com/run-llama/liteparse)|11.5k|A fast, helpful, and open-source document parser|\n|[bisheng](https://github.com/dataelement/bisheng)|11.5k|BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.|\n|[edge-tts](https://github.com/rany2/edge-tts)|11.5k|Use Microsoft Edge's online text-to-speech service from Python WITHOUT needing Microsoft Edge or Windows or an API key|\n|[Toonflow-app](https://github.com/HBAI-Ltd/Toonflow-app)|11.5k|Toonflow 是开源一站式 AI 短剧创作工具，将小说、剧本快速转化为动画短剧。集成 AI 编剧、智能分镜、角色与视频生成，跨平台桌面端轻量部署，助力创作者低成本批量产出视觉内容。Toonflow is an open-source AI tool that turns stories and scripts into animated short dramas. Features AI scriptwriting, storyboarding, character and video generation. A cross-platform desktop app for efficient content creation.|\n|[chandra](https://github.com/datalab-to/chandra)|11.5k|OCR model that handles complex tables, forms, handwriting with full layout.|\n|[dive-into-machine-learning](https://github.com/dive-into-machine-learning/dive-into-machine-learning)|11.4k|Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)|\n|[agents](https://github.com/livekit/agents)|11.4k|A framework for building realtime voice AI agents 🤖🎙️📹|\n|[yolov10](https://github.com/THU-MIG/yolov10)|11.3k|YOLOv10: Real-Time End-to-End Object Detection [NeurIPS 2024]|\n|[ai-toolkit](https://github.com/ostris/ai-toolkit)|11.3k|The ultimate training toolkit for finetuning diffusion models|\n|[DALLE2-pytorch](https://github.com/lucidrains/DALLE2-pytorch)|11.3k|Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch|\n|[kornia](https://github.com/kornia/kornia)|11.3k|🐍 Geometric Computer Vision Library for Spatial AI|\n|[LAVIS](https://github.com/salesforce/LAVIS)|11.3k|LAVIS - A One-stop Library for Language-Vision Intelligence|\n|[piper](https://github.com/rhasspy/piper)|11.2k|A fast, local neural text to speech system|\n|[wechat-bot](https://github.com/wangrongding/wechat-bot)|11.2k|🤖 Multi-platform IM AI Agent for Telegram, WhatsApp, Lark, and WeChat. Connects ChatGPT / Claude / Kimi / DeepSeek / Ollama / Pi for auto-replies, community analysis, contact management, and inactive-friend detection.|\n|[stylegan2](https://github.com/NVlabs/stylegan2)|11.2k|StyleGAN2 - Official TensorFlow Implementation|\n|[convnetjs](https://github.com/karpathy/convnetjs)|11.2k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[promptflow](https://github.com/microsoft/promptflow)|11.2k|Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.|\n|[wandb](https://github.com/wandb/wandb)|11.2k|The AI developer platform. 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Track everything from the corporate/private jets of the wealthy, and spy satellites, to seismic events in one unified interface. Hook an AI agent up to have it parse through data and find previously unseen correlations. The knowledge is available to all but rarely aggregated in the open, until now.|\n|[models](https://github.com/onnx/models)|9.7k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[Bob](https://github.com/ripperhe/Bob)|9.7k|Bob 是一款 macOS 平台的翻译和 OCR 软件。|\n|[fff](https://github.com/dmtrKovalenko/fff)|9.7k|The fastest and the most accurate file search SDK for AI agents, Neovim, Rust, C, Python, Bun and NodeJS|\n|[gpt-prompt-engineer](https://github.com/mshumer/gpt-prompt-engineer)|9.7k||\n|[udlbook](https://github.com/udlbook/udlbook)|9.6k|Understanding Deep Learning - Simon J.D. 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Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.|\n|[einops](https://github.com/arogozhnikov/einops)|9.5k|Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)|\n|[TextBlob](https://github.com/sloria/TextBlob)|9.5k|Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.|\n|[langchaingo](https://github.com/tmc/langchaingo)|9.5k|LangChain for Go, the easiest way to write LLM-based programs in Go|\n|[ralph-claude-code](https://github.com/frankbria/ralph-claude-code)|9.5k|Autonomous AI development loop for Claude Code with intelligent exit detection|\n|[warriorjs](https://github.com/olistic/warriorjs)|9.5k|🏰 An exciting game of programming and Artificial Intelligence|\n|[hamuleite](https://github.com/hoochanlon/hamuleite)|9.5k|🏔️国立台湾大学、新加坡国立大学、早稻田大学、东京大学，中央研究院（台湾）以及中国重点高校及科研机构，社科、经济、数学、博弈论、哲学、系统工程类学术论文等知识库。|\n|[garden-skills](https://github.com/ConardLi/garden-skills)|9.5k|ConardLi's open-source Skills collection, featuring web design, knowledge retrieval, image generation, and more.|\n|[all-in-rag](https://github.com/datawhalechina/all-in-rag)|9.5k|🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/|\n|[facechain](https://github.com/modelscope/facechain)|9.5k|FaceChain is a deep-learning toolchain for generating your Digital-Twin.|\n|[ChatRWKV](https://github.com/BlinkDL/ChatRWKV)|9.5k|ChatRWKV is like ChatGPT but powered by RWKV (100% RNN) language model, and open source.|\n|[openbrowser](https://github.com/ntegrals/openbrowser)|9.5k|Let AI agents browse the web. 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Enterprise-Grade Unified LLM Gateway Support for 200+ Models And 35+ Providers, Load Balacing w/ Priority-base Routing, Cost Management, Chat Share, Cloud Sync, Credit/Subscription Billing, All File Parsing, Web Search, Built-in Model Cache.|\n|[deeplake](https://github.com/activeloopai/deeplake)|9.2k|Deeplake is AI Data Runtime for Agents. 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Supports computation on CPU and GPU.|\n|[pyro](https://github.com/pyro-ppl/pyro)|9k|Deep universal probabilistic programming with Python and PyTorch|\n|[TinyLlama](https://github.com/jzhang38/TinyLlama)|9k|The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.|\n|[dots.ocr](https://github.com/rednote-hilab/dots.ocr)|9k|Multilingual Document Layout Parsing in a Single Vision-Language Model|\n|[cnn-explainer](https://github.com/poloclub/cnn-explainer)|9k|Learning Convolutional Neural Networks with Interactive Visualization.|\n|[apex](https://github.com/NVIDIA/apex)|9k|A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch|\n|[morphic](https://github.com/miurla/morphic)|9k|An AI-powered search engine with a generative UI|\n|[speech_recognition](https://github.com/Uberi/speech_recognition)|9k|Speech recognition module for Python, supporting several engines and APIs, online and offline.|\n|[clone-voice](https://github.com/jianchang512/clone-voice)|9k|A sound cloning tool with a web interface, using your voice or any sound to record audio / 一个带web界面的声音克隆工具，使用你的音色或任意声音来录制音频|\n|[evolution-api](https://github.com/evolution-foundation/evolution-api)|9k|Evolution API is an open-source WhatsApp integration API|\n|[Noi](https://github.com/lencx/Noi)|9k|🚀 Less chaos. 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It can effectively overcome the shortcomings of the traditional RAG vector similarity calculation model.|\n|[state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems)|8.9k|This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.|\n|[evolver](https://github.com/EvoMap/evolver)|8.9k|The GEP-powered self-evolving engine for AI agents. 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The user can ask a question and the system will make a multi engine search and combine the search result to LLM and generate the answer based on search results. It's all FREE to use.|\n|[introtodeeplearning](https://github.com/MITDeepLearning/introtodeeplearning)|8.7k|Lab Materials for MIT 6.S191: Introduction to Deep Learning|\n|[BentoML](https://github.com/bentoml/BentoML)|8.7k|The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!|\n|[local-deep-research](https://github.com/LearningCircuit/local-deep-research)|8.7k|~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. 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Basically ChatGPT but with PaLM|\n|[EdgeGPT](https://github.com/acheong08/EdgeGPT)|7.9k|Reverse engineered API of Microsoft's Bing Chat AI|\n|[faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch)|7.9k|A faster pytorch implementation of faster r-cnn|\n|[ailab](https://github.com/microsoft/ailab)|7.8k|Experience, Learn and Code the latest breakthrough innovations with Microsoft AI|\n|[machine-learning-yearning-cn](https://github.com/deeplearning-ai/machine-learning-yearning-cn)|7.8k|Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著|\n|[stanza](https://github.com/stanfordnlp/stanza)|7.8k|Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages|\n|[Yi](https://github.com/01-ai/Yi)|7.8k|A series of large language models trained from scratch by developers @01-ai|\n|[tensorrtx](https://github.com/wang-xinyu/tensorrtx)|7.8k|Implementation of popular deep learning networks with TensorRT network definition API|\n|[tensorflow2_tutorials_chinese](https://github.com/czy36mengfei/tensorflow2_tutorials_chinese)|7.8k|tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials|\n|[html-anything](https://github.com/nexu-io/html-anything)|7.8k|✨ The agentic HTML editor — your local AI agent writes the HTML, you ship it. 🚀 75 Skills × 9 Surfaces (magazine · deck · poster · XHS / tweet · prototype · data report · Hyperframes) 🛡️ Sandboxed preview · 📤 1-click to WeChat / X / Zhihu / HTML / PNG 🔑 Zero API key — Claude Code / Cursor / Codex / Gemini / Copilot / OpenCode / Qwen / Aider.|\n|[loop-engineering](https://github.com/cobusgreyling/loop-engineering)|7.8k|Practical patterns, starters & CLI tools for loop engineering with AI coding agents. 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It turns CLI-based AI orchestration into a desktop experience without using the terminal. China website is https://clawx.com.cn.|\n|[mlx-audio](https://github.com/Blaizzy/mlx-audio)|7.5k|A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.|\n|[Ultra-Light-Fast-Generic-Face-Detector-1MB](https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB)|7.5k|💎1MB lightweight face detection model (1MB轻量级人脸检测模型)|\n|[MeloTTS](https://github.com/myshell-ai/MeloTTS)|7.5k|High-quality multi-lingual text-to-speech library by MyShell.ai. 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Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.|\n|[forgecode](https://github.com/tailcallhq/forgecode)|7.5k|AI enabled pair programmer for Claude, GPT, O Series, Grok, Deepseek, Gemini and 300+ models|\n|[slime](https://github.com/THUDM/slime)|7.5k|slime is an LLM post-training framework for RL Scaling.|\n|[gpt-neox](https://github.com/EleutherAI/gpt-neox)|7.4k|An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries|\n|[InfiniteTalk](https://github.com/MeiGen-AI/InfiniteTalk)|7.4k|​​Unlimited-length talking video generation​​ that supports image-to-video and video-to-video generation|\n|[mmagic](https://github.com/open-mmlab/mmagic)|7.4k|OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. 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Steel Browser is a batteries-included browser sandbox that lets you automate the web without worrying about infrastructure.|\n|[class-transformer](https://github.com/typestack/class-transformer)|7.3k|Decorator-based transformation, serialization, and deserialization between objects and classes.|\n|[stable-diffusion-webui-docker](https://github.com/AbdBarho/stable-diffusion-webui-docker)|7.3k|Easy Docker setup for Stable Diffusion with user-friendly UI|\n|[hertzbeat](https://github.com/apache/hertzbeat)|7.3k|An AI-powered next-generation open source real-time observability system.|\n|[openllmetry](https://github.com/traceloop/openllmetry)|7.3k|Open-source observability for your GenAI or LLM application, based on OpenTelemetry|\n|[open-codesign](https://github.com/OpenCoworkAI/open-codesign)|7.3k|Open-source Claude Design alternative. One-click import your Claude Code / Codex API key. Prompt → prototype / slides / PDF. Multi-model (Claude, GPT, Gemini, Kimi, GLM, Ollama). 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The most effective open source solution to turn your pdf files in a chatbot!|\n|[sdnext](https://github.com/vladmandic/sdnext)|7.2k|SD.Next: All-in-one WebUI for AI generative image and video creation, captioning and processing|\n|[GLM-OCR](https://github.com/zai-org/GLM-OCR)|7.2k|GLM-OCR: Accurate × Fast × Comprehensive|\n|[RapidOCR](https://github.com/RapidAI/RapidOCR)|7.2k|📄 Awesome OCR multiple programing languages toolkits based on ONNX Runtime, OpenVINO, MNN, PaddlePaddle, TensorRT and PyTorch.|\n|[guardrails](https://github.com/guardrails-ai/guardrails)|7.1k|Adding guardrails to large language models.|\n|[flyte](https://github.com/flyteorg/flyte)|7.1k|Dynamic, resilient AI orchestration. 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Written in PyTorch.|\n|[YuE](https://github.com/multimodal-art-projection/YuE)|6.3k|YuE: Open Full-song Music Generation Foundation Model, something similar to Suno.ai but open|\n|[docs](https://github.com/tensorflow/docs)|6.3k|TensorFlow documentation|\n|[StyleTTS2](https://github.com/yl4579/StyleTTS2)|6.3k|StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models|\n|[TagUI](https://github.com/aisingapore/TagUI)|6.3k|Free RPA tool by AI Singapore|\n|[DictionaryByGPT4](https://github.com/Ceelog/DictionaryByGPT4)|6.3k|一本 GPT4 生成的单词书📚，超过 8000 个单词分析，涵盖了词义、例句、词根词缀、变形、文化背景、记忆技巧和小故事|\n|[Lihang](https://github.com/SmirkCao/Lihang)|6.3k|Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]|\n|[zero-to-mastery-ml](https://github.com/mrdbourke/zero-to-mastery-ml)|6.3k|All course materials for the Zero to Mastery Machine Learning and Data Science course.|\n|[pytext](https://github.com/facebookresearch/pytext)|6.3k|A natural language modeling framework based on PyTorch|\n|[mlx-lm](https://github.com/ml-explore/mlx-lm)|6.3k|Run LLMs with MLX|\n|[trafilatura](https://github.com/adbar/trafilatura)|6.3k|Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML|\n|[tensorpack](https://github.com/tensorpack/tensorpack)|6.3k|A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility|\n|[BossSensor](https://github.com/Hironsan/BossSensor)|6.3k|Hide screen when boss is approaching.|\n|[chinese-llm-benchmark](https://github.com/jeinlee1991/chinese-llm-benchmark)|6.3k|非线智能 NoneLinear - ReLE评测：中文AI大模型能力评测（持续更新）：目前已囊括374个大模型，覆盖chatgpt、gpt-5.4、谷歌gemini-3.1-pro、Claude-4.6、文心ERNIE-X1.1、ERNIE-5.0、qwen3.6-max、qwen3.6-plus、百川、讯飞星火、商汤senseChat等商用模型， 以及step3.5-flash、kimi-k2.6、ernie4.5、MiniMax-M2.7、deepseek-v4、Qwen3.6、llama4、智谱GLM-5.1、MiMo-V2、LongCat、gemma4、mistral等开源大模型。不仅提供排行榜，也提供规模超200万的大模型缺陷库！方便广大社区研究分析、改进大模型。|\n|[deepo](https://github.com/ufoym/deepo)|6.3k|Setup and customize deep learning environment in seconds.|\n|[chatgpt-mac](https://github.com/vincelwt/chatgpt-mac)|6.3k|ChatGPT for Mac, living in your menubar.|\n|[argos-translate](https://github.com/argosopentech/argos-translate)|6.3k|Open-source offline translation library written in Python|\n|[open-deep-research](https://github.com/nickscamara/open-deep-research)|6.3k|An open source deep research clone. 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Serves as datastore for https://latent.space writing, and product brainstorming, but has cleaned up canonical references under the /Resources folder.|\n|[Orpheus-TTS](https://github.com/canopyai/Orpheus-TTS)|6.2k|Towards Human-Sounding Speech|\n|[nanodet](https://github.com/RangiLyu/nanodet)|6.2k|NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥|\n|[gpt-fast](https://github.com/meta-pytorch/gpt-fast)|6.2k|Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.|\n|[CapsWriter-Offline](https://github.com/HaujetZhao/CapsWriter-Offline)|6.2k|PC 端语音输入工具，离线识别，高准确率、低延迟，支持热词、LLM润色。按住CapsLock或鼠标侧键X2说话，松开自动上屏。|\n|[HyperLPR](https://github.com/szad670401/HyperLPR)|6.2k|High Performance Chinese License Plate Recognition Framework.|\n|[RealChar](https://github.com/Shaunwei/RealChar)|6.2k|🎙️🤖Create, Customize and Talk to your AI Character/Companion in Realtime (All in One Codebase!). 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Uses current app context, multiple LLMs, and MCP tools to help you act across apps.|\n|[speech-to-speech](https://github.com/huggingface/speech-to-speech)|6.2k|Build local voice agents with open-source models|\n|[llm](https://github.com/rustformers/llm)|6.2k|[Unmaintained, see README] An ecosystem of Rust libraries for working with large language models|\n|[PufferLib](https://github.com/PufferAI/PufferLib)|6.1k|Puffing up reinforcement learning|\n|[BibiGPT-v1](https://github.com/JimmyLv/BibiGPT-v1)|6.1k|BibiGPT v1 · one-Click AI Summary for Audio/Video & Chat with Learning Content: Bilibili \\| YouTube \\| Tweet丨TikTok丨Dropbox丨Google Drive丨Local files \\| Websites丨Podcasts \\| Meetings \\| Lectures, etc. 音视频内容 AI 一键总结 & 对话：哔哩哔哩丨YouTube丨推特丨小红书丨抖音丨快手丨百度网盘丨阿里云盘丨网页丨播客丨会议丨本地文件等 (原 BiliGPT 省流神器 & AI课代表)|\n|[darkflow](https://github.com/thtrieu/darkflow)|6.1k|Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices|\n|[apfel](https://github.com/Arthur-Ficial/apfel)|6.1k|The free AI already on your Mac. CLI tool, OpenAI-compatible server, and interactive chat — all on-device via Apple Intelligence. No API keys, no cloud, no downloads.|\n|[CodePilot](https://github.com/op7418/CodePilot)|6.1k|A multi-model AI agent desktop client — connect any AI provider, extend with MCP & skills, control from your phone. Built with Electron + Next.js.|\n|[swift](https://github.com/tensorflow/swift)|6.1k|Swift for TensorFlow|\n|[UGATIT](https://github.com/taki0112/UGATIT)|6.1k|Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)|\n|[Yuxi](https://github.com/xerrors/Yuxi)|6.1k|结合知识库、知识图谱管理的 多租户 Agent Harness 平台。 An agent harness that integrates a LightRAG knowledge base and knowledge graphs. Build with LangChain + Vue + FastAPI, support DeepAgents、MinerU PDF、Neo4j 、MCP.|\n|[chineseocr](https://github.com/chineseocr/chineseocr)|6.1k|yolo3+ocr|\n|[AI-Job-Notes](https://github.com/amusi/AI-Job-Notes)|6.1k|AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）|\n|[tts-vue](https://github.com/LokerL/tts-vue)|6.1k|🎤 微软语音合成工具，使用 Electron + Vue + ElementPlus + Vite 构建。|\n|[adversarial-robustness-toolbox](https://github.com/Trusted-AI/adversarial-robustness-toolbox)|6.1k|Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams|\n|[neutts](https://github.com/neuphonic/neutts)|6.1k|On-device TTS model by Neuphonic|\n|[deepchat](https://github.com/ThinkInAIXYZ/deepchat)|6.1k|🐬DeepChat - A smart assistant that connects powerful AI to your personal world|\n|[tsai](https://github.com/timeseriesAI/tsai)|6.1k|Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai \\| State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai|\n|[FATE](https://github.com/FederatedAI/FATE)|6.1k|An Industrial Grade Federated Learning Framework|\n|[MegaTTS3](https://github.com/bytedance/MegaTTS3)|6.1k||\n|[gogocode](https://github.com/thx/gogocode)|6.1k|GoGoCode is a transformer for JavaScript/Typescript/HTML based on AST but providing a more intuitive API.|\n|[lit-llama](https://github.com/Lightning-AI/lit-llama)|6.1k|Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.|\n|[lora-scripts](https://github.com/Akegarasu/lora-scripts)|6.1k|SD-Trainer. LoRA & Dreambooth training scripts & GUI use kohya-ss's trainer, for diffusion model.|\n|[zcf](https://github.com/UfoMiao/zcf)|6.1k|Zero-Config Code Flow for Claude code & Codex|\n|[AIOS](https://github.com/agiresearch/AIOS)|6.1k|AIOS: AI Agent Operating System|\n|[app-store-screenshots](https://github.com/ParthJadhav/app-store-screenshots)|6.1k|end to end app store screenshot creation using AI|\n|[AI-Project-Gallery](https://github.com/KalyanM45/AI-Project-Gallery)|6.1k|This Repository Contain All the Artificial Intelligence Projects such as Machine Learning, Deep Learning and Generative AI that I have done while understanding Advanced Techniques & Concepts.|\n|[LaWGPT](https://github.com/pengxiao-song/LaWGPT)|6.1k|🎉 Repo for LaWGPT, Chinese-Llama tuned with Chinese Legal knowledge. 基于中文法律知识的大语言模型|\n|[nerf-pytorch](https://github.com/yenchenlin/nerf-pytorch)|6k|A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.|\n|[rikkahub](https://github.com/rikkahub/rikkahub)|6k|RikkaHub is an Android APP that supports for multiple LLM providers.|\n|[atomic-agents](https://github.com/Eigenwise/atomic-agents)|6k|Building AI agents, atomically|\n|[Swift-AI](https://github.com/Swift-AI/Swift-AI)|6k|The Swift machine learning library.|\n|[autoclip](https://github.com/zhouxiaoka/autoclip)|6k|AutoClip : AI-powered video clipping and highlight generation · 一款智能高光提取与剪辑的二创工具|\n|[opencvsharp](https://github.com/shimat/opencvsharp)|6k|OpenCV wrapper for .NET|\n|[opensquilla](https://github.com/opensquilla/opensquilla)|6k|OpenSquilla — Token-Efficient AI Agent with same budget, higher intelligence density|\n|[TensorFlow-Tutorials](https://github.com/nlintz/TensorFlow-Tutorials)|6k|Simple tutorials using Google's TensorFlow Framework|\n|[tree-of-thought-llm](https://github.com/princeton-nlp/tree-of-thought-llm)|6k|[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models|\n|[PINNs](https://github.com/maziarraissi/PINNs)|6k|Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations|\n|[tiny-dnn](https://github.com/tiny-dnn/tiny-dnn)|6k|header only, dependency-free deep learning framework in C++14|\n|[open_nsfw](https://github.com/yahoo/open_nsfw)|6k|Not Suitable for Work (NSFW) classification using deep neural network Caffe models.|\n|[silero-models](https://github.com/snakers4/silero-models)|6k|Silero Models: pre-trained text-to-speech models made embarrassingly simple|\n|[VLM-R1](https://github.com/om-ai-lab/VLM-R1)|6k|Solve Visual Understanding with Reinforced VLMs|\n|[ai-deadlines](https://github.com/paperswithcode/ai-deadlines)|6k|:alarm_clock: AI conference deadline countdowns|\n|[snorkel](https://github.com/snorkel-team/snorkel)|6k|A system for quickly generating training data with weak supervision|\n|[enchanted](https://github.com/gluonfield/enchanted)|6k|Enchanted is iOS and macOS app for chatting with private self hosted language models such as Llama2, Mistral or Vicuna using Ollama.|\n|[bb-browser](https://github.com/epiral/bb-browser)|6k|Your browser is the API. CLI + MCP server for AI agents to control Chrome with your login state.|\n|[Chinese-CLIP](https://github.com/OFA-Sys/Chinese-CLIP)|6k|Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.|\n|[honcho](https://github.com/plastic-labs/honcho)|6k|Memory library for building stateful agents|\n|[DevOpsGPT](https://github.com/kuafuai/DevOpsGPT)|6k|Multi agent system for AI-driven software development. Combine LLM with DevOps tools to convert natural language requirements into working software. Supports any development language and extends the existing code.|\n|[flashinfer](https://github.com/flashinfer-ai/flashinfer)|6k|FlashInfer: Kernel Library for LLM Serving|\n|[ai_quant_trade](https://github.com/charliedream1/ai_quant_trade)|6k|股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、大模型、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易|\n|[LLocalSearch](https://github.com/nilsherzig/LLocalSearch)|6k|LLocalSearch is a completely locally running search aggregator using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed.|\n|[helicone](https://github.com/Helicone/helicone)|5.9k|🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓|\n|[agents](https://github.com/aiwaves-cn/agents)|5.9k|An Open-source Framework for Data-centric, Self-evolving Autonomous Language Agents|\n|[n8n-free-templates](https://github.com/wassupjay/n8n-free-templates)|5.9k|A curated set of 200+ plug-and-play n8n workflows that fuse classic automation with today’s AI stack—vector DBs, embeddings, and LLMs. Import any JSON, add your creds, hit Activate, and you’re live. 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Find their Instagram, FB and Twitter Profiles using Image Recognition and Reverse Image Search.|\n|[sketch-code](https://github.com/ashnkumar/sketch-code)|5.1k|Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.|\n|[moco](https://github.com/facebookresearch/moco)|5.1k|PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722|\n|[whereami](https://github.com/kootenpv/whereami)|5.1k|Uses WiFi signals :signal_strength: and machine learning to predict where you are|\n|[Augmentor](https://github.com/mdbloice/Augmentor)|5.1k|Image augmentation library in Python for machine learning.|\n|[Viper](https://github.com/FunnyWolf/Viper)|5.1k|Adversary simulation and Red teaming platform with AI|\n|[kaolin](https://github.com/NVIDIAGameWorks/kaolin)|5.1k|A PyTorch Library for Accelerating 3D Deep Learning Research|\n|[PasteMD](https://github.com/RICHQAQ/PasteMD)|5.1k|一键将 Markdown 和网页 AI 对话（ChatGPT/DeepSeek等）完美粘贴到 Word、WPS 和 Excel 的效率工具 \\| One-click paste Markdown and AI responses (ChatGPT/DeepSeek) into Word, WPS, and Excel perfectly.|\n|[Realtime_Multi-Person_Pose_Estimation](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation)|5.1k|Code repo for realtime multi-person pose estimation in CVPR'17 (Oral)|\n|[CyberStrikeAI](https://github.com/Ed1s0nZ/CyberStrikeAI)|5.1k|The system of action for AI-native cybersecurity—where intent becomes governed execution, evidence becomes operational memory, and every operation improves the next.|\n|[pytorch-template](https://github.com/victoresque/pytorch-template)|5.1k|PyTorch deep learning projects made easy.|\n|[agents-cli](https://github.com/google/agents-cli)|5.1k|The CLI and skills that turn any coding assistant into an expert at creating, evaluating, and deploying AI agents on Google Cloud.|\n|[have-fun-with-machine-learning](https://github.com/humphd/have-fun-with-machine-learning)|5.1k|An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks|\n|[copilot](https://github.com/opencx-labs/copilot)|5.1k||\n|[maths-cs-ai-compendium](https://github.com/HenryNdubuaku/maths-cs-ai-compendium)|5.1k|Become a cracked AI/ML Research Engineer|\n|[Synonyms](https://github.com/chatopera/Synonyms)|5.1k|:herb: 中文近义词：聊天机器人，智能问答工具包|\n|[Object-Detection-Metrics](https://github.com/rafaelpadilla/Object-Detection-Metrics)|5.1k|Most popular metrics used to evaluate object detection algorithms.|\n|[lightfm](https://github.com/lyst/lightfm)|5.1k|A Python implementation of LightFM, a hybrid recommendation algorithm.|\n|[IDM-VTON](https://github.com/yisol/IDM-VTON)|5.1k|[ECCV2024] IDM-VTON : Improving Diffusion Models for Authentic Virtual Try-on in the Wild|\n|[Search-R1](https://github.com/PeterGriffinJin/Search-R1)|5.1k|Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL|\n|[mmaction2](https://github.com/open-mmlab/mmaction2)|5.1k|OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark|\n|[clarity-upscaler](https://github.com/philz1337x/clarity-upscaler)|5.1k|Clarity AI \\| AI Image Upscaler & Enhancer - free and open-source Magnific Alternative|\n|[graph-based-deep-learning-literature](https://github.com/naganandy/graph-based-deep-learning-literature)|5.1k|links to conference publications in graph-based deep learning|\n|[pix2pix-tensorflow](https://github.com/affinelayer/pix2pix-tensorflow)|5.1k|Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/|\n|[YouDub-webui](https://github.com/liuzhao1225/YouDub-webui)|5.1k|开源 AI 视频本地化工具：自动完成 YouTube/Bilibili 视频下载、字幕识别与翻译、语音克隆配音、音轨混合和字幕压制。|\n|[AgentVerse](https://github.com/OpenBMB/AgentVerse)|5.1k|🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation|\n|[semantic-segmentation-pytorch](https://github.com/CSAILVision/semantic-segmentation-pytorch)|5.1k|Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset|\n|[pytorch-OpCounter](https://github.com/Lyken17/pytorch-OpCounter)|5.1k|Count the MACs / FLOPs of your PyTorch model.|\n|[chatgpt2api](https://github.com/basketikun/chatgpt2api)|5.1k|ChatGPT官网接口纯协议的逆向实现，支持GPT-Image-2模型、文本模型，兼容OpenAI接口协议，在线批量生图/编辑图，号池管理，支持可编辑PPT/PSD文件逆向，支持导入CPA、sub2api号池 、支持接入Cherry Studio、New Api 等软件|\n|[cube-studio](https://github.com/tencentmusic/cube-studio)|5.1k|cube studio开源云原生一站式机器学习/深度学习/大模型AI平台，mlops算法链路全流程，算力租赁平台，notebook在线开发，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务VGPU虚拟化，边缘计算，标注平台自动化标注，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库，AI模型市场，支持国产cpu/gpu/npu 昇腾生态，支持RDMA，支持pytorch/tf/mxnet/deepspeed/paddle/colossalai/horovod/ray/volcano等分布式|\n|[AutoGPTQ](https://github.com/AutoGPTQ/AutoGPTQ)|5.1k|An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.|\n|[VideoCrafter](https://github.com/AILab-CVC/VideoCrafter)|5.1k|VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models|\n|[rocketride-server](https://github.com/rocketride-org/rocketride-server)|5.1k|High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.|\n|[EasyR1](https://github.com/hiyouga/EasyR1)|5.1k|EasyR1: An Efficient, Scalable, Multi-Modality RL Training Framework based on veRL|\n|[lms](https://github.com/lmstudio-ai/lms)|5.1k|LM Studio CLI|\n|[Roadmap-To-Learn-Generative-AI-In-2025](https://github.com/krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025)|5.1k||\n|[super-gradients](https://github.com/Deci-AI/super-gradients)|5.1k|Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.|\n|[Olares](https://github.com/beclab/Olares)|5.1k|Olares: An Open-Source Personal Cloud to Reclaim Your Data|\n|[danfojs](https://github.com/javascriptdata/danfojs)|5k|Danfo.js is an open source, JavaScript library providing high performance, intuitive, and easy to use data structures for manipulating and processing structured data.|\n|[guizang-social-card-skill](https://github.com/op7418/guizang-social-card-skill)|5k|🪧 Claude Code / Codex skill — generate Xiaohongshu carousels & WeChat 21:9+1:1 cover pairs. Editorial × Swiss visual systems, 28 layouts, 10 themes, single-file HTML → PNG. 小红书图文 + 公众号封面对|\n|[dmls-book](https://github.com/chiphuyen/dmls-book)|5k|Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)|\n|[mace](https://github.com/XiaoMi/mace)|5k|MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.|\n|[h2o-llmstudio](https://github.com/h2oai/h2o-llmstudio)|5k|H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/|\n|[argilla](https://github.com/argilla-io/argilla)|5k|Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets|\n|[llm-answer-engine](https://github.com/developersdigest/llm-answer-engine)|5k|Perplexity Inspired Answer Engine|\n|[json_repair](https://github.com/mangiucugna/json_repair)|5k|Repair malformed JSON from LLMs, APIs, logs, and user input in Python.|\n|[python-machine-learning-book-3rd-edition](https://github.com/rasbt/python-machine-learning-book-3rd-edition)|5k|The \"Python Machine Learning (3rd edition)\" book code repository|\n|[machine_learning_complete](https://github.com/Nyandwi/machine_learning_complete)|5k|A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.|\n|[gaianet-node](https://github.com/GaiaNet-AI/gaianet-node)|5k|Install, run and deploy your own decentralized AI agent service|\n|[VITS-fast-fine-tuning](https://github.com/Plachtaa/VITS-fast-fine-tuning)|5k|This repo is a pipeline of VITS finetuning for fast speaker adaptation TTS, and many-to-many voice conversion|\n|[DeepSeek-V2](https://github.com/deepseek-ai/DeepSeek-V2)|5k|DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model|\n|[marqo](https://github.com/marqo-ai/marqo)|5k|Ecommerce Search and Discovery - marqo.ai|\n|[mcp-ui](https://github.com/MCP-UI-Org/mcp-ui)|5k|UI over MCP. Create next-gen UI experiences with the protocol and SDK!|\n"}, "f197899d3b54bad6613bfa0137787c5b73280c95": {"t": 1785772691.7543786, "n": 103556, "h": "e4d8cf91efad1d69", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2020.07.09\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow](https://github.com/tensorflow/tensorflow)|146k|An Open Source Machine Learning Framework for Everyone|\n|[keras](https://github.com/keras-team/keras)|48.9k|Deep Learning for humans|\n|[opencv](https://github.com/opencv/opencv)|46.1k|Open Source Computer Vision Library|\n|[pytorch](https://github.com/pytorch/pytorch)|40k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|38.1k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[tesseract](https://github.com/tesseract-ocr/tesseract)|35.3k|Tesseract Open Source OCR Engine (main repository)|\n|[face_recognition](https://github.com/ageitgey/face_recognition)|35.2k|The world's simplest facial recognition api for Python and the command line|\n|[faceswap](https://github.com/deepfakes/faceswap)|31.4k|Deepfakes Software For All|\n|[transformers](https://github.com/huggingface/transformers)|30.4k|🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.|\n|[100-Days-Of-ML-Code](https://github.com/Avik-Jain/100-Days-Of-ML-Code)|29.1k|100 Days of ML Coding|\n|[julia](https://github.com/JuliaLang/julia)|28.1k|The Julia Language: A fresh approach to technical computing.|\n|[gold-miner](https://github.com/xitu/gold-miner)|26.6k|🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：|\n|[awesome-scalability](https://github.com/binhnguyennus/awesome-scalability)|26.6k|The Patterns of Scalable, Reliable, and Performant Large-Scale Systems|\n|[basics](https://github.com/madewithml/basics)|24.5k|📚 Learn ML with clean code, simplified math and illustrative visuals.|\n|[bert](https://github.com/google-research/bert)|23.9k|TensorFlow code and pre-trained models for BERT|\n|[funNLP](https://github.com/fighting41love/funNLP)|22.1k|(Machine Learning)NLP面试中常考到的知识点和代码实现、nlp4han:中文自然语言处理工具集(断句/分词/词性标注/组块/句法分析/语义分析/NER/N元语法/HMM/代词消解/情感分析/拼写检查、XLM：Face…|\n|[xgboost](https://github.com/dmlc/xgboost)|19.4k|Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow|\n|[Real-Time-Voice-Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning)|18.4k|Clone a voice in 5 seconds to generate arbitrary speech in real-time|\n|[d2l-zh](https://github.com/d2l-ai/d2l-zh)|17.9k|《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。|\n|[openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose)|17.8k|OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation|\n|[Coursera-ML-AndrewNg-Notes](https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes)|17.7k|吴恩达老师的机器学习课程个人笔记|\n|[DeepFaceLab](https://github.com/iperov/DeepFaceLab)|17.3k|DeepFaceLab is the leading software for creating deepfakes.|\n|[pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|17.3k|PyTorch Tutorial for Deep Learning Researchers|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|17.2k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[spaCy](https://github.com/explosion/spaCy)|16.8k|💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython|\n|[NLP-progress](https://github.com/sebastianruder/NLP-progress)|16.2k|Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.|\n|[100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|15.6k|100-Days-Of-ML-Code中文版|\n|[cs-video-courses](https://github.com/Developer-Y/cs-video-courses)|14.9k|List of Computer Science courses with video lectures.|\n|[WaveFunctionCollapse](https://github.com/mxgmn/WaveFunctionCollapse)|14.7k|Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics.|\n|[lectures](https://github.com/oxford-cs-deepnlp-2017/lectures)|14.7k|Oxford Deep NLP 2017 course|\n|[reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|14.7k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[pwc](https://github.com/zziz/pwc)|14.7k|Papers with code. Sorted by stars. Updated weekly.|\n|[TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|14.6k|Simple and ready-to-use tutorials for TensorFlow|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|14.4k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[pumpkin-book](https://github.com/datawhalechina/pumpkin-book)|14k|《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book|\n|[tfjs](https://github.com/tensorflow/tfjs)|13.5k|A WebGL accelerated JavaScript library for training and deploying ML models.|\n|[examples](https://github.com/pytorch/examples)|13.5k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[openface](https://github.com/cmusatyalab/openface)|13.5k|Face recognition with deep neural networks.|\n|[Qix](https://github.com/ty4z2008/Qix)|13.3k|Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang|\n|[spleeter](https://github.com/deezer/spleeter)|12.7k|Deezer source separation library including pretrained models.|\n|[Virgilio](https://github.com/virgili0/Virgilio)|12.7k|Your new Mentor for Data Science E-Learning.|\n|[nndl.github.io](https://github.com/nndl/nndl.github.io)|12.7k|《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning|\n|[Screenshot-to-code](https://github.com/emilwallner/Screenshot-to-code)|12.7k|A neural network that transforms a design mock-up into a static website.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|12.4k|Image-to-Image Translation in PyTorch|\n|[pytorch-handbook](https://github.com/zergtant/pytorch-handbook)|11.9k|pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行|\n|[gun](https://github.com/amark/gun)|11.9k|An open source cybersecurity protocol for syncing decentralized graph data.|\n|[Paddle](https://github.com/PaddlePaddle/Paddle)|11.8k|PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训…|\n|[tensorflow-zh](https://github.com/jikexueyuanwiki/tensorflow-zh)|11.8k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[darknet](https://github.com/AlexeyAB/darknet)|11.4k|YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )|\n|[learnopencv](https://github.com/spmallick/learnopencv)|11.4k|Learn OpenCV : C++ and Python Examples|\n|[neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|11.3k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[google-research](https://github.com/google-research/google-research)|11.2k|Google Research|\n|[labelImg](https://github.com/tzutalin/labelImg)|11.2k|🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images|\n|[gensim](https://github.com/RaRe-Technologies/gensim)|11k|Topic Modelling for Humans|\n|[pix2code](https://github.com/tonybeltramelli/pix2code)|10.9k|pix2code: Generating Code from a Graphical User Interface Screenshot|\n|[facenet](https://github.com/davidsandberg/facenet)|10.8k|Face recognition using Tensorflow|\n|[DeOldify](https://github.com/jantic/DeOldify)|10.7k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.7k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning)|10.6k|VIP cheatsheets for Stanford's CS 229 Machine Learning|\n|[mmdetection](https://github.com/open-mmlab/mmdetection)|10.5k|OpenMMLab Detection Toolbox and Benchmark|\n|[face-api.js](https://github.com/justadudewhohacks/face-api.js)|10.4k|JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js|\n|[Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list)|10.4k|A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,t…|\n|[nsfw_data_scraper](https://github.com/alex000kim/nsfw_data_scraper)|10.2k|Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier|\n|[convnetjs](https://github.com/karpathy/convnetjs)|10k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[CycleGAN](https://github.com/junyanz/CycleGAN)|9.8k|Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.|\n|[streamlit](https://github.com/streamlit/streamlit)|9.8k|Streamlit — The fastest way to build data apps in Python|\n|[DeepCreamPy](https://github.com/deeppomf/DeepCreamPy)|9.7k|Decensoring Hentai with Deep Neural Networks|\n|[stylegan](https://github.com/NVlabs/stylegan)|9.7k|StyleGAN - Official TensorFlow Implementation|\n|[Dive-into-DL-PyTorch](https://github.com/ShusenTang/Dive-into-DL-PyTorch)|9.6k|本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。|\n|[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|9.6k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[horovod](https://github.com/horovod/horovod)|9.6k|Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.|\n|[Deep-Learning-with-TensorFlow-book](https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book)|9.4k|深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.|\n|[neural-doodle](https://github.com/alexjc/neural-doodle)|9.4k|Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! 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The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.|\n|[Bender](https://github.com/xmartlabs/Bender)|1.7k|Easily craft fast Neural Networks on iOS! Use TensorFlow models. 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Support training on your own dataset.|\n|[TensorFlow.NET](https://github.com/SciSharp/TensorFlow.NET)|1.3k|.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C#.|\n|[pytextrank](https://github.com/DerwenAI/pytextrank)|1.3k|Python implementation of TextRank for phrase extraction and summarization of text documents|\n|[infer](https://github.com/dotnet/infer)|1.3k|Infer.NET is a framework for running Bayesian inference in graphical models|\n|[uda](https://github.com/google-research/uda)|1.3k|Unsupervised Data Augmentation (UDA)|\n|[mmaction](https://github.com/open-mmlab/mmaction)|1.3k|An open-source toolbox for action understanding based on PyTorch|\n|[spark-nlp](https://github.com/JohnSnowLabs/spark-nlp)|1.3k|State of the Art Natural Language Processing|\n|[pytorch-semantic-segmentation](https://github.com/zijundeng/pytorch-semantic-segmentation)|1.3k|PyTorch for Semantic 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Scenarios|\n|[Deep-Image-Analogy](https://github.com/msracver/Deep-Image-Analogy)|1.2k|The source code of 'Visual Attribute Transfer through Deep Image Analogy'.|\n|[spektral](https://github.com/danielegrattarola/spektral)|1.2k|Graph Neural Networks with Keras and Tensorflow 2.|\n|[DeepAA](https://github.com/OsciiArt/DeepAA)|1.2k|make ASCII Art by Deep Learning|\n|[vvedenie-mashinnoe-obuchenie](https://github.com/demidovakatya/vvedenie-mashinnoe-obuchenie)|1.2k|📝 Подборка ресурсов по машинному обучению|\n|[OpenSeq2Seq](https://github.com/NVIDIA/OpenSeq2Seq)|1.2k|Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP|\n|[Forge](https://github.com/hollance/Forge)|1.2k|A neural network toolkit for Metal|\n|[keras-yolo3](https://github.com/experiencor/keras-yolo3)|1.2k|Training and Detecting Objects with YOLO3|\n|[NiftyNet](https://github.com/NifTK/NiftyNet)|1.2k|[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy|\n|[Awesome-TensorFlow-Chinese](https://github.com/fendouai/Awesome-TensorFlow-Chinese)|1.2k|Awesome-TensorFlow-Chinese，TensorFlow 中文资源精选，官方网站，安装教程，入门教程，视频教程，实战项目，学习路径。QQ群：167122861，公众号：磐创AI，微信群二维码：http://www.tensorflownews.com/|\n|[StudyBook](https://github.com/changwookjun/StudyBook)|1.2k|Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)|\n|[awesome-semantic-segmentation-pytorch](https://github.com/Tramac/awesome-semantic-segmentation-pytorch)|1.2k|Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)|\n|[RFBNet](https://github.com/ruinmessi/RFBNet)|1.2k|Receptive Field Block Net for Accurate and Fast Object Detection, ECCV 2018|\n|[GPflow](https://github.com/GPflow/GPflow)|1.2k|Gaussian processes in TensorFlow|\n|[dlwpt-code](https://github.com/deep-learning-with-pytorch/dlwpt-code)|1.2k|Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.|\n|[dlcv_for_beginners](https://github.com/frombeijingwithlove/dlcv_for_beginners)|1.2k|《深度学习与计算机视觉》配套代码|\n|[Deep-Learning-with-PyTorch-Tutorials](https://github.com/dragen1860/Deep-Learning-with-PyTorch-Tutorials)|1.2k|深度学习与PyTorch入门实战视频教程 配套源代码和PPT|\n|[DLTK](https://github.com/DLTK/DLTK)|1.2k|Deep Learning Toolkit for Medical Image Analysis|\n|[FCN.tensorflow](https://github.com/shekkizh/FCN.tensorflow)|1.2k|Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)|\n|[facenet-pytorch](https://github.com/timesler/facenet-pytorch)|1.2k|Pretrained Pytorch face detection (MTCNN) and recognition (InceptionResnet) models|\n|[h2o-tutorials](https://github.com/h2oai/h2o-tutorials)|1.2k|Tutorials and training material for the H2O Machine Learning Platform|\n|[nlp-journey](https://github.com/msgi/nlp-journey)|1.2k|Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc. All codes are implemented intensorflow 2.0.|\n|[object_detector_app](https://github.com/datitran/object_detector_app)|1.2k|Real-Time Object Recognition App with Tensorflow and OpenCV|\n|[tnt](https://github.com/pytorch/tnt)|1.2k|Simple tools for logging and visualizing, loading and training|\n|[tensorflow-deeplab-resnet](https://github.com/DrSleep/tensorflow-deeplab-resnet)|1.2k|DeepLab-ResNet rebuilt in TensorFlow|\n|[reproducible-image-denoising-state-of-the-art](https://github.com/wenbihan/reproducible-image-denoising-state-of-the-art)|1.2k|Collection of popular and reproducible image denoising works.|\n|[senet.pytorch](https://github.com/moskomule/senet.pytorch)|1.2k|PyTorch implementation of SENet|\n|[pytorch-seq2seq](https://github.com/IBM/pytorch-seq2seq)|1.2k|An open source framework for seq2seq models in PyTorch.|\n|[efficient_densenet_pytorch](https://github.com/gpleiss/efficient_densenet_pytorch)|1.2k|A memory-efficient implementation of DenseNets|\n|[pytorch-retinanet](https://github.com/yhenon/pytorch-retinanet)|1.2k|Pytorch implementation of RetinaNet object detection.|\n|[cakechat](https://github.com/lukalabs/cakechat)|1.2k|CakeChat: Emotional Generative Dialog System|\n|[pytorch-fcn](https://github.com/wkentaro/pytorch-fcn)|1.2k|PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)|\n|[python-machine-learning-book-3rd-edition](https://github.com/rasbt/python-machine-learning-book-3rd-edition)|1.2k|The \"Python Machine Learning (3rd edition)\" book code repository|\n|[tf-quant-finance](https://github.com/google/tf-quant-finance)|1.2k|High-performance TensorFlow library for quantitative finance.|\n|[gnes](https://github.com/gnes-ai/gnes)|1.1k|GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.|\n|[Image-OutPainting](https://github.com/bendangnuksung/Image-OutPainting)|1.1k|🏖 Keras Implementation of Painting outside the box|\n|[Fabrik](https://github.com/Cloud-CV/Fabrik)|1.1k|🏭 Collaboratively build, visualize, and design neural nets in browser|\n|[attention-transfer](https://github.com/szagoruyko/attention-transfer)|1.1k|Improving Convolutional Networks via Attention Transfer (ICLR 2017)|\n|[pytorch-cifar100](https://github.com/weiaicunzai/pytorch-cifar100)|1.1k|Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)|\n|[MONAI](https://github.com/Project-MONAI/MONAI)|1.1k|AI Toolkit for Healthcare Imaging|\n|[tensorrec](https://github.com/jfkirk/tensorrec)|1.1k|A TensorFlow recommendation algorithm and framework in Python.|\n|[mleap](https://github.com/combust/mleap)|1.1k|MLeap: Deploy Spark Pipelines to Production|\n|[noreward-rl](https://github.com/pathak22/noreward-rl)|1.1k|[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning|\n|[PyTorchNLPBook](https://github.com/joosthub/PyTorchNLPBook)|1.1k|Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info|\n|[mtcnn](https://github.com/ipazc/mtcnn)|1.1k|MTCNN face detection implementation for TensorFlow, as a PIP package.|\n|[WaveRNN](https://github.com/fatchord/WaveRNN)|1.1k|WaveRNN Vocoder + TTS|\n|[UNet-family](https://github.com/ShawnBIT/UNet-family)|1.1k|Paper and implementation of UNet-related model.|\n|[Awesome-pytorch-list-CNVersion](https://github.com/xavier-zy/Awesome-pytorch-list-CNVersion)|1.1k|Awesome-pytorch-list 翻译工作进行中......|\n|[tensorflow-fcn](https://github.com/MarvinTeichmann/tensorflow-fcn)|1.1k|An Implementation of Fully Convolutional Networks in Tensorflow.|\n|[BicycleGAN](https://github.com/junyanz/BicycleGAN)|1.1k|Toward Multimodal Image-to-Image Translation|\n|[TensorFlow2.0-Examples](https://github.com/YunYang1994/TensorFlow2.0-Examples)|1.1k|🙄 Difficult algorithm, simple code.|\n|[fast-autoaugment](https://github.com/kakaobrain/fast-autoaugment)|1.1k|Official Implementation of 'Fast AutoAugment' in PyTorch.|\n|[fastai_deeplearn_part1](https://github.com/reshamas/fastai_deeplearn_part1)|1.1k|Notes for Fastai Deep Learning Course|\n|[HyperGAN](https://github.com/HyperGAN/HyperGAN)|1.1k|Composable GAN framework with api and user interface|\n|[home](https://github.com/apachecn/home)|1.1k|ApacheCN 开源组织：公告、介绍、成员、活动、交流方式|\n|[tfx](https://github.com/tensorflow/tfx)|1.1k|TFX is an end-to-end platform for deploying production ML pipelines|\n|[handwriting-synthesis](https://github.com/sjvasquez/handwriting-synthesis)|1.1k|Handwriting Synthesis with RNNs ✏️|\n|[image-quality-assessment](https://github.com/idealo/image-quality-assessment)|1.1k|Convolutional Neural Networks to predict the aesthetic and technical quality of images.|\n|[PerceptualSimilarity](https://github.com/richzhang/PerceptualSimilarity)|1.1k|Learned Perceptual Image Patch Similarity (LPIPS) metric. In CVPR, 2018.|\n|[lanenet-lane-detection](https://github.com/MaybeShewill-CV/lanenet-lane-detection)|1.1k|Unofficial implemention of lanenet model for real time lane detection using deep neural network model https://maybeshewill-cv.github.io/lanenet-lane-detection/|\n|[uTensor](https://github.com/uTensor/uTensor)|1.1k|TinyML AI inference library|\n|[torchgan](https://github.com/torchgan/torchgan)|1.1k|Research Framework for easy and efficient training of GANs based on Pytorch|\n|[merlin](https://github.com/CSTR-Edinburgh/merlin)|1.1k|This is now the official location of the Merlin project.|\n|[CLUE](https://github.com/CLUEbenchmark/CLUE)|1k|中文语言理解基准测评 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard|\n|[tfjs-node](https://github.com/tensorflow/tfjs-node)|1k|TensorFlow powered JavaScript library for training and deploying ML models on Node.js.|\n|[CycleGAN-TensorFlow](https://github.com/vanhuyz/CycleGAN-TensorFlow)|1k|An implementation of CycleGan using TensorFlow|\n|[EffectivePyTorch](https://github.com/vahidk/EffectivePyTorch)|1k|PyTorch tutorials and best practices.|\n|[hercules](https://github.com/src-d/hercules)|1k|Gaining advanced insights from Git repository history.|\n|[AdvancedEAST](https://github.com/huoyijie/AdvancedEAST)|1k|AdvancedEAST is an algorithm used for Scene image text detect, which is primarily based on EAST, and the significant improvement was also made, which make long text predictions more accurate.|\n|[one-pixel-attack-keras](https://github.com/Hyperparticle/one-pixel-attack-keras)|1k|Keras implementation of \"One pixel attack for fooling deep neural networks\" using differential evolution on Cifar10 and ImageNet|\n|[CRNN_Chinese_Characters_Rec](https://github.com/Sierkinhane/CRNN_Chinese_Characters_Rec)|1k|(CRNN) Chinese Characters Recognition.|\n|[hmtl](https://github.com/huggingface/hmtl)|1k|🌊HMTL: Hierarchical Multi-Task Learning - A State-of-the-Art neural network model for several NLP tasks based on PyTorch and AllenNLP|\n|[rethinking-network-pruning](https://github.com/Eric-mingjie/rethinking-network-pruning)|1k|Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)|\n|[pytorch-classification](https://github.com/bearpaw/pytorch-classification)|1k|Classification with PyTorch.|\n|[a-PyTorch-Tutorial-to-Image-Captioning](https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning)|1k|Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning|\n|[reformer-pytorch](https://github.com/lucidrains/reformer-pytorch)|1k|Reformer, the efficient Transformer, in Pytorch|\n|[pytorch-YOLOv4](https://github.com/Tianxiaomo/pytorch-YOLOv4)|1k|PyTorch ,ONNX and TensorRT implementation of YOLOv4|\n|[FaceMaskDetection](https://github.com/AIZOOTech/FaceMaskDetection)|1k|开源人脸口罩检测模型和数据 Detect faces and determine whether people are wearing mask.|\n|[gen-efficientnet-pytorch](https://github.com/rwightman/gen-efficientnet-pytorch)|1k|Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS|\n|[open-reid](https://github.com/Cysu/open-reid)|1k|Open source person re-identification library in python|\n|[wgan-gp](https://github.com/caogang/wgan-gp)|1k|A pytorch implementation of Paper \"Improved Training of Wasserstein GANs\"|\n\n"}, "fbe8d7a66f8f83632b3a999c17e65d8fb127ed40": {"t": 1785772715.1504781, "n": 46662, "h": "150e626edda45318", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2019.08.15\n\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow](https://github.com/tensorflow/tensorflow)|133k|An Open Source Machine Learning Framework for Everyone|\n|[models](https://github.com/tensorflow/models)|56.5k|Models and examples built with TensorFlow|\n|[keras](https://github.com/keras-team/keras)|43.5k|Deep Learning for humans|\n|[scikit-learn](https://github.com/scikit-learn/scikit-learn)|36.6k|scikit-learn: machine learning in Python|\n|[TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|33.4k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[pytorch](https://github.com/pytorch/pytorch)|30.8k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[caffe](https://github.com/BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[practicalAI](https://github.com/GokuMohandas/practicalAI)|19.6k|📚 A practical approach to machine learning.|\n|[incubator-mxnet](https://github.com/apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[bert](https://github.com/google-research/bert)|17.4k|TensorFlow code and pre-trained models for BERT|\n|[CNTK](https://github.com/microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[handson-ml](https://github.com/ageron/handson-ml)|16.3k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[fastai](https://github.com/fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.5k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.9k|PyTorch Tutorial for Deep Learning Researchers|\n|[homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|12.2k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.9k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[Virgilio](https://github.com/virgili0/Virgilio)|11.6k|Your new Mentor for Data Science E-Learning.|\n|[funNLP](https://github.com/fighting41love/funNLP)|11.6k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[deeplearning4j](https://github.com/eclipse/deeplearning4j)|11.1k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.8k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.3k|Image-to-Image Translation in PyTorch|\n|[LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[ChatterBot](https://github.com/gunthercox/ChatterBot)|8.8k|ChatterBot is a machine learning, conversational dialog engine for creating chat bots|\n|[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[tensor2tensor](https://github.com/tensorflow/tensor2tensor)|8.6k|Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.|\n|[caffe2](https://github.com/facebookarchive/caffe2)|8.5k|Caffe2 is a lightweight, modular, and scalable deep learning framework.|\n|[DeepCreamPy](https://github.com/deeppomf/DeepCreamPy)|8.3k|Decensoring Hentai with Deep Neural Networks|\n|[fast-style-transfer](https://github.com/lengstrom/fast-style-transfer)|8.2k|TensorFlow CNN for fast style transfer ⚡🖥🎨🖼|\n|[dopamine](https://github.com/google/dopamine)|8.2k|Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.|\n|[dlib](https://github.com/davisking/dlib)|7.8k|A toolkit for making real world machine learning and data analysis applications in C++|\n|[sonnet](https://github.com/deepmind/sonnet)|7.8k|TensorFlow-based neural network library|\n|[deep-learning-with-python-notebooks](https://github.com/fchollet/deep-learning-with-python-notebooks)|7.7k|Jupyter notebooks for the code samples of the book \"Deep Learning with Python\"|\n|[MLAlgorithms](https://github.com/rushter/MLAlgorithms)|7.6k|Minimal and clean examples of machine learning algorithms implementations|\n|[DeOldify](https://github.com/jantic/DeOldify)|7.6k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[stylegan](https://github.com/NVlabs/stylegan)|7.5k|StyleGAN - 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Load trained weights, retrain/fine-tune using tensorflow, export constant graph def …|\n|[faceai](https://github.com/vipstone/faceai)|4.9k|一款入门级的人脸、视频、文字检测以及识别的项目.|\n|[cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf)|4.9k|Convolutional Neural Network for Text Classification in Tensorflow|\n|[seq2seq](https://github.com/google/seq2seq)|4.9k|A general-purpose encoder-decoder framework for Tensorflow|\n|[pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch)|4.9k|Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.|\n|[pytorch_geometric](https://github.com/rusty1s/pytorch_geometric)|4.8k|Geometric Deep Learning Extension Library for PyTorch|\n|[have-fun-with-machine-learning](https://github.com/humphd/have-fun-with-machine-learning)|4.8k|An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks|\n|[nmt](https://github.com/tensorflow/nmt)|4.8k|TensorFlow Neural Machine Translation Tutorial|\n|[neural-style](https://github.com/anishathalye/neural-style)|4.8k|Neural style in TensorFlow! 🎨|\n|[tensorpack](https://github.com/tensorpack/tensorpack)|4.7k|A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility|\n|[keras-js](https://github.com/transcranial/keras-js)|4.6k|Run Keras models in the browser, with GPU support using WebGL|\n|[python-machine-learning-book-2nd-edition](https://github.com/rasbt/python-machine-learning-book-2nd-edition)|4.6k|The \"Python Machine Learning (2nd edition)\" book code repository and info resource|\n|[aerosolve](https://github.com/airbnb/aerosolve)|4.6k|A machine learning package built for humans.|\n|[TopDeepLearning](https://github.com/aymericdamien/TopDeepLearning)|4.5k|A list of popular github projects related to deep learning|\n|[swift](https://github.com/tensorflow/swift)|4.5k|Swift for TensorFlow Project Home Page|\n|[TensorFlow-World](https://github.com/astorfi/TensorFlow-World)|4.4k|🌎 Simple and ready-to-use tutorials for TensorFlow|\n|[TensorFlow-Book](https://github.com/BinRoot/TensorFlow-Book)|4.3k|Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.|\n|[xlnet](https://github.com/zihangdai/xlnet)|4.3k|XLNet: Generalized Autoregressive Pretraining for Language Understanding|\n|[edward](https://github.com/blei-lab/edward)|4.3k|A probabilistic programming language in TensorFlow. Deep generative models, variational inference.|\n|[alluxio](https://github.com/Alluxio/alluxio)|4.3k|Alluxio, data orchestration for analytics and machine learning in the cloud|\n|[stargan](https://github.com/yunjey/stargan)|4.1k|Official PyTorch Implementation of StarGAN - CVPR 2018|\n|[keras-rl](https://github.com/keras-rl/keras-rl)|4.1k|Deep Reinforcement Learning for Keras.|\n|[sketch-code](https://github.com/ashnkumar/sketch-code)|4k|Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to dra…|\n|[PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN)|3.9k|PyTorch implementations of Generative Adversarial Networks.|\n|[tensorspace](https://github.com/tensorspace-team/tensorspace)|3.9k|Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained dee…|\n|[nlp-tutorial](https://github.com/graykode/nlp-tutorial)|3.9k|Natural Language Processing Tutorial for Deep Learning Researchers|\n|[MMdnn](https://github.com/microsoft/MMdnn)|3.9k|MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion a…|\n|[photoprism](https://github.com/photoprism/photoprism)|3.9k|Personal Photo Management powered by Go and Google TensorFlow|\n|[faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch)|3.9k|A faster pytorch implementation of faster r-cnn|\n|[pix2pixHD](https://github.com/NVIDIA/pix2pixHD)|3.8k|Synthesizing and manipulating 2048x1024 images with conditional GANs|\n|[pipeline](https://github.com/PipelineAI/pipeline)|3.7k|PipelineAI: Real-Time Enterprise AI Platform|\n|[serving](https://github.com/tensorflow/serving)|3.7k|A flexible, high-performance serving system for machine learning models|\n|[PySyft](https://github.com/OpenMined/PySyft)|3.7k|A library for encrypted, privacy preserving deep learning|\n|[DeepLearningZeroToAll](https://github.com/hunkim/DeepLearningZeroToAll)|3.6k|TensorFlow Basic Tutorial Labs|\n|[graph_nets](https://github.com/deepmind/graph_nets)|3.6k|Build Graph Nets in Tensorflow|\n|[practical-pytorch](https://github.com/spro/practical-pytorch)|3.5k|PyTorch tutorials demonstrating modern techniques with readable code|\n|[CapsNet-Tensorflow](https://github.com/naturomics/CapsNet-Tensorflow)|3.5k|A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules|\n|[tensorflow-docs](https://github.com/xitu/tensorflow-docs)|3.5k|TensorFlow 最新官方文档中文版|\n|[PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|3.5k|Build your neural network easy and fast|\n|[DeepPavlov](https://github.com/deepmipt/DeepPavlov)|3.3k|An open source library for deep learning end-to-end dialog systems and chatbots.|\n|[Tensorflow-Tutorial](https://github.com/MorvanZhou/Tensorflow-Tutorial)|3.3k|Tensorflow tutorial from basic to hard|\n|[SSD-Tensorflow](https://github.com/balancap/SSD-Tensorflow)|3.3k|Single Shot MultiBox Detector in TensorFlow|\n|[Practical_RL](https://github.com/yandexdataschool/Practical_RL)|3.3k|A course in reinforcement learning in the wild|\n|[tensorflow-generative-model-collections](https://github.com/hwalsuklee/tensorflow-generative-model-collections)|3.3k|Collection of generative models in Tensorflow|\n|[OpenNMT-py](https://github.com/OpenNMT/OpenNMT-py)|3.3k|Open Source Neural Machine Translation in PyTorch|\n|[TensorFlowOnSpark](https://github.com/yahoo/TensorFlowOnSpark)|3.2k|TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.|\n|[hands-on-ml-zh](https://github.com/apachecn/hands-on-ml-zh)|3.1k|📖 [译] Sklearn 与 TensorFlow 机器学习实用指南【版权问题，网站已下线！！】|\n|[Learning-to-See-in-the-Dark](https://github.com/cchen156/Learning-to-See-in-the-Dark)|3.1k|Learning to See in the Dark. 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Datasets and Neural Network Layers)|\n|[DeblurGAN](https://github.com/KupynOrest/DeblurGAN)|1.4k|Image Deblurring using Generative Adversarial Networks|\n|[NeuroNER](https://github.com/Franck-Dernoncourt/NeuroNER)|1.3k|Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.|\n|[tf_unet](https://github.com/jakeret/tf_unet)|1.3k|Generic U-Net Tensorflow implementation for image segmentation|\n|[torchsample](https://github.com/ncullen93/torchsample)|1.3k|High-Level Training, Data Augmentation, and Utilities for Pytorch|\n|[models](https://github.com/onnx/models)|1.3k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[CADL](https://github.com/pkmital/CADL)|1.3k|Course materials/Homework materials for the FREE MOOC course on \"Creative Applications of Deep Learning w/ Tensorflow…|\n|[CoreML-in-ARKit](https://github.com/hanleyweng/CoreML-in-ARKit)|1.3k|Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit…|\n|[DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[BerryNet](https://github.com/DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[pai](https://github.com/microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "ceaa357ce1e93c05e513fe98cf0ca828e3158f6f": {"t": 1785772716.5599883, "n": 44868, "h": "98de5e6f23c94a13", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2018.08.14\n\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow](https://github.com/tensorflow/tensorflow)|133k|An Open Source Machine Learning Framework for Everyone|\n|[models](https://github.com/tensorflow/models)|56.5k|Models and examples built with TensorFlow|\n|[keras](https://github.com/keras-team/keras)|43.4k|Deep Learning for humans|\n|[scikit-learn](https://github.com/scikit-learn/scikit-learn)|36.6k|scikit-learn: machine learning in Python|\n|[TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|33.4k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[pytorch](https://github.com/pytorch/pytorch)|30.8k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[caffe](https://github.com/BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[practicalAI](https://github.com/GokuMohandas/practicalAI)|19.5k|📚 A practical approach to machine learning.|\n|[incubator-mxnet](https://github.com/apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[bert](https://github.com/google-research/bert)|17.4k|TensorFlow code and pre-trained models for BERT|\n|[CNTK](https://github.com/microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[handson-ml](https://github.com/ageron/handson-ml)|16.3k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[fastai](https://github.com/fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.5k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.9k|PyTorch Tutorial for Deep Learning Researchers|\n|[homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|12.1k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[Virgilio](https://github.com/virgili0/Virgilio)|11.6k|Your new Mentor for Data Science E-Learning.|\n|[funNLP](https://github.com/fighting41love/funNLP)|11.5k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[deeplearning4j](https://github.com/eclipse/deeplearning4j)|11.1k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.8k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.3k|Image-to-Image Translation in PyTorch|\n|[LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[turicreate](https://github.com/apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[ChatterBot](https://github.com/gunthercox/ChatterBot)|8.8k|ChatterBot is a machine learning, conversational dialog engine for creating chat bots|\n|[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[tensor2tensor](https://github.com/tensorflow/tensor2tensor)|8.6k|Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.|\n|[caffe2](https://github.com/facebookarchive/caffe2)|8.5k|Caffe2 is a lightweight, modular, and scalable deep learning framework.|\n|[DeepCreamPy](https://github.com/deeppomf/DeepCreamPy)|8.3k|Decensoring Hentai with Deep Neural Networks|\n|[fast-style-transfer](https://github.com/lengstrom/fast-style-transfer)|8.2k|TensorFlow CNN for fast style transfer ⚡🖥🎨🖼|\n|[dopamine](https://github.com/google/dopamine)|8.2k|Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.|\n|[sonnet](https://github.com/deepmind/sonnet)|7.8k|TensorFlow-based neural network library|\n|[dlib](https://github.com/davisking/dlib)|7.7k|A toolkit for making real world machine learning and data analysis applications in C++|\n|[deep-learning-with-python-notebooks](https://github.com/fchollet/deep-learning-with-python-notebooks)|7.7k|Jupyter notebooks for the code samples of the book \"Deep Learning with Python\"|\n|[MLAlgorithms](https://github.com/rushter/MLAlgorithms)|7.6k|Minimal and clean examples of machine learning algorithms implementations|\n|[stylegan](https://github.com/NVlabs/stylegan)|7.5k|StyleGAN - Official TensorFlow Implementation|\n|[TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials)|7.5k|TensorFlow Tutorials with YouTube Videos|\n|[DeOldify](https://github.com/jantic/DeOldify)|7.5k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[kubeflow](https://github.com/kubeflow/kubeflow)|7.3k|Machine Learning Toolkit for Kubernetes|\n|[php-ml](https://github.com/php-ai/php-ml)|7.3k|PHP-ML - Machine Learning library for PHP|\n|[horovod](https://github.com/horovod/horovod)|7.2k|Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.|\n|[pattern](https://github.com/clips/pattern)|7.1k|Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysi…|\n|[allennlp](https://github.com/allenai/allennlp)|6.9k|An open-source NLP research library, built on PyTorch.|\n|[flair](https://github.com/zalandoresearch/flair)|6.9k|A very simple framework for state-of-the-art Natural Language Processing (NLP)|\n|[pytorch-handbook](https://github.com/zergtant/pytorch-handbook)|6.7k|pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行|\n|[golearn](https://github.com/sjwhitworth/golearn)|6.7k|Machine Learning for Go|\n|[imgaug](https://github.com/aleju/imgaug)|6.7k|Image augmentation for machine learning experiments.|\n|[vid2vid](https://github.com/NVIDIA/vid2vid)|6.7k|Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.|\n|[face-api.js](https://github.com/justadudewhohacks/face-api.js)|6.6k|JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js|\n|[tutorials](https://github.com/MorvanZhou/tutorials)|6.6k|机器学习相关教程|\n|[onnx](https://github.com/onnx/onnx)|6.6k|Open Neural Network Exchange|\n|[mit-deep-learning-book-pdf](https://github.com/janishar/mit-deep-learning-book-pdf)|6.5k|MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville|\n|[vowpal_wabbit](https://github.com/VowpalWabbit/vowpal_wabbit)|6.5k|Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as onli…|\n|[ml-agents](https://github.com/Unity-Technologies/ml-agents)|6.5k|Unity Machine Learning Agents Toolkit|\n|[numpy-ml](https://github.com/ddbourgin/numpy-ml)|6.4k|Machine learning, in numpy|\n|[machinelearning](https://github.com/dotnet/machinelearning)|6.3k|ML.NET is an open source and cross-platform machine learning framework for .NET.|\n|[lime](https://github.com/marcotcr/lime)|6.3k|Lime: Explaining the predictions of any machine learning classifier|\n|[rasa](https://github.com/RasaHQ/rasa)|6.2k|💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, c…|\n|[maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark)|6.2k|Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.|\n|[tpot](https://github.com/EpistasisLab/tpot)|6.1k|A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.|\n|[shap](https://github.com/slundberg/shap)|6.1k|A unified approach to explain the output of any machine learning model.|\n|[DCGAN-tensorflow](https://github.com/carpedm20/DCGAN-tensorflow)|6k|A tensorflow implementation of \"Deep Convolutional Generative Adversarial Networks\"|\n|[machine-learning-course](https://github.com/machinelearningmindset/machine-learning-course)|5.9k|💬 Machine Learning Course with Python. Refer to the course page for step-by-step explanations.|\n|[autokeras](https://github.com/keras-team/autokeras)|5.8k|Accessible AutoML for deep learning.|\n|[netron](https://github.com/lutzroeder/netron)|5.8k|Visualizer for neural network, deep learning and machine learning models|\n|[mmdetection](https://github.com/open-mmlab/mmdetection)|5.7k|Open MMLab Detection Toolbox and Benchmark|\n|[facets](https://github.com/PAIR-code/facets)|5.7k|Visualizations for machine learning datasets|\n|[ludwig](https://github.com/uber/ludwig)|5.6k|Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to…|\n|[Swift-AI](https://github.com/Swift-AI/Swift-AI)|5.6k|The Swift machine learning library.|\n|[DeepFaceLab](https://github.com/iperov/DeepFaceLab)|5.6k|DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. Includes prebuilt ready to work stan…|\n|[mit-deep-learning](https://github.com/lexfridman/mit-deep-learning)|5.6k|Tutorials, assignments, and competitions for MIT Deep Learning related courses.|\n|[pytorch-book](https://github.com/chenyuntc/pytorch-book)|5.5k|PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation|\n|[pyro](https://github.com/pyro-ppl/pyro)|5.5k|Deep universal probabilistic programming with Python and PyTorch|\n|[generative-models](https://github.com/wiseodd/generative-models)|5.4k|Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.|\n|[guess](https://github.com/guess-js/guess)|5.4k|Libraries & tools for enabling Machine Learning driven user-experiences on the web|\n|[tensorboardX](https://github.com/lanpa/tensorboardX)|5.4k|tensorboard for pytorch (and chainer, mxnet, numpy, ...)|\n|[tensorlayer](https://github.com/tensorlayer/tensorlayer)|5.4k|Deep Learning and Reinforcement Learning Library for Scientists|\n|[bullet3](https://github.com/bulletphysics/bullet3)|5.3k|Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics,|\n|[pytext](https://github.com/facebookresearch/pytext)|5.3k|A natural language modeling framework based on PyTorch|\n|[tensorflow_cookbook](https://github.com/nfmcclure/tensorflow_cookbook)|5.1k|Code for Tensorflow Machine Learning Cookbook|\n|[text_classification](https://github.com/brightmart/text_classification)|5.1k|all kinds of text classification models and more with deep learning|\n|[fairseq](https://github.com/pytorch/fairseq)|5k|Facebook AI Research Sequence-to-Sequence Toolkit written in Python.|\n|[deepo](https://github.com/ufoym/deepo)|5k|Set up deep learning environment in a single command line.|\n|[bert-as-service](https://github.com/hanxiao/bert-as-service)|5k|Mapping a variable-length sentence to a fixed-length vector using BERT model|\n|[darkflow](https://github.com/thtrieu/darkflow)|5k|Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def …|\n|[faceai](https://github.com/vipstone/faceai)|4.9k|一款入门级的人脸、视频、文字检测以及识别的项目.|\n|[cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf)|4.9k|Convolutional Neural Network for Text Classification in Tensorflow|\n|[seq2seq](https://github.com/google/seq2seq)|4.9k|A general-purpose encoder-decoder framework for Tensorflow|\n|[pretrained-models.pytorch](https://github.com/Cadene/pretrained-models.pytorch)|4.9k|Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.|\n|[pytorch_geometric](https://github.com/rusty1s/pytorch_geometric)|4.8k|Geometric Deep Learning Extension Library for PyTorch|\n|[have-fun-with-machine-learning](https://github.com/humphd/have-fun-with-machine-learning)|4.8k|An absolute beginner's guide to Machine Learning and Image Classification with Neural Networks|\n|[nmt](https://github.com/tensorflow/nmt)|4.8k|TensorFlow Neural Machine Translation Tutorial|\n|[neural-style](https://github.com/anishathalye/neural-style)|4.8k|Neural style in TensorFlow! 🎨|\n|[tensorpack](https://github.com/tensorpack/tensorpack)|4.7k|A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility|\n|[keras-js](https://github.com/transcranial/keras-js)|4.6k|Run Keras models in the browser, with GPU support using WebGL|\n|[python-machine-learning-book-2nd-edition](https://github.com/rasbt/python-machine-learning-book-2nd-edition)|4.6k|The \"Python Machine Learning (2nd edition)\" book code repository and info resource|\n|[aerosolve](https://github.com/airbnb/aerosolve)|4.6k|A machine learning package built for humans.|\n|[TopDeepLearning](https://github.com/aymericdamien/TopDeepLearning)|4.5k|A list of popular github projects related to deep learning|\n|[swift](https://github.com/tensorflow/swift)|4.5k|Swift for TensorFlow Project Home Page|\n|[TensorFlow-World](https://github.com/astorfi/TensorFlow-World)|4.4k|🌎 Simple and ready-to-use tutorials for TensorFlow|\n|[TensorFlow-Book](https://github.com/BinRoot/TensorFlow-Book)|4.3k|Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.|\n|[xlnet](https://github.com/zihangdai/xlnet)|4.3k|XLNet: Generalized Autoregressive Pretraining for Language Understanding|\n|[edward](https://github.com/blei-lab/edward)|4.3k|A probabilistic programming language in TensorFlow. Deep generative models, variational inference.|\n|[alluxio](https://github.com/Alluxio/alluxio)|4.3k|Alluxio, data orchestration for analytics and machine learning in the cloud|\n|[keras-rl](https://github.com/keras-rl/keras-rl)|4.1k|Deep Reinforcement Learning for Keras.|\n|[stargan](https://github.com/yunjey/stargan)|4k|Official PyTorch Implementation of StarGAN - CVPR 2018|\n|[sketch-code](https://github.com/ashnkumar/sketch-code)|4k|Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to dra…|\n|[PyTorch-GAN](https://github.com/eriklindernoren/PyTorch-GAN)|3.9k|PyTorch implementations of Generative Adversarial Networks.|\n|[tensorspace](https://github.com/tensorspace-team/tensorspace)|3.9k|Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained dee…|\n|[nlp-tutorial](https://github.com/graykode/nlp-tutorial)|3.9k|Natural Language Processing Tutorial for Deep Learning Researchers|\n|[MMdnn](https://github.com/microsoft/MMdnn)|3.9k|MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion a…|\n|[photoprism](https://github.com/photoprism/photoprism)|3.9k|Personal Photo Management powered by Go and Google TensorFlow|\n|[faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch)|3.9k|A faster pytorch implementation of faster r-cnn|\n|[pix2pixHD](https://github.com/NVIDIA/pix2pixHD)|3.8k|Synthesizing and manipulating 2048x1024 images with conditional GANs|\n|[pipeline](https://github.com/PipelineAI/pipeline)|3.7k|PipelineAI: Real-Time Enterprise AI Platform|\n|[serving](https://github.com/tensorflow/serving)|3.7k|A flexible, high-performance serving system for machine learning models|\n|[PySyft](https://github.com/OpenMined/PySyft)|3.7k|A library for encrypted, privacy preserving deep learning|\n|[DeepLearningZeroToAll](https://github.com/hunkim/DeepLearningZeroToAll)|3.6k|TensorFlow Basic Tutorial Labs|\n|[graph_nets](https://github.com/deepmind/graph_nets)|3.6k|Build Graph Nets in Tensorflow|\n|[practical-pytorch](https://github.com/spro/practical-pytorch)|3.5k|PyTorch tutorials demonstrating modern techniques with readable code|\n|[CapsNet-Tensorflow](https://github.com/naturomics/CapsNet-Tensorflow)|3.5k|A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules|\n|[tensorflow-docs](https://github.com/xitu/tensorflow-docs)|3.5k|TensorFlow 最新官方文档中文版|\n|[PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial)|3.5k|Build your neural network easy and fast|\n|[DeepPavlov](https://github.com/deepmipt/DeepPavlov)|3.3k|An open source library for deep learning end-to-end dialog systems and chatbots.|\n|[Tensorflow-Tutorial](https://github.com/MorvanZhou/Tensorflow-Tutorial)|3.3k|Tensorflow tutorial from basic to hard|\n|[SSD-Tensorflow](https://github.com/balancap/SSD-Tensorflow)|3.3k|Single Shot MultiBox Detector in TensorFlow|\n|[Practical_RL](https://github.com/yandexdataschool/Practical_RL)|3.3k|A course in reinforcement learning in the wild|\n|[tensorflow-generative-model-collections](https://github.com/hwalsuklee/tensorflow-generative-model-collections)|3.3k|Collection of generative models in Tensorflow|\n|[TensorFlowOnSpark](https://github.com/yahoo/TensorFlowOnSpark)|3.2k|TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.|\n|[hands-on-ml-zh](https://github.com/apachecn/hands-on-ml-zh)|3.1k|📖 [译] Sklearn 与 TensorFlow 机器学习实用指南【版权问题，网站已下线！！】|\n|[Learning-to-See-in-the-Dark](https://github.com/cchen156/Learning-to-See-in-the-Dark)|3.1k|Learning to See in the Dark. 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Flux is the ML library that doesn't make you tensor|\n|[deepschool.io](https://github.com/sachinruk/deepschool.io)|1.6k|Deep Learning tutorials in jupyter notebooks.|\n|[tacotron](https://github.com/keithito/tacotron)|1.6k|A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)|\n|[VoTT](https://github.com/microsoft/VoTT)|1.6k|Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.|\n|[euler](https://github.com/alibaba/euler)|1.6k|A distributed graph deep learning framework.|\n|[nnvm](https://github.com/dmlc/nnvm)|1.6k|move to https://github.com/dmlc/tvm/|\n|[dm_control](https://github.com/deepmind/dm_control)|1.6k|The DM Control Suite and Package is a tool for developing and testing reinforcement learning agents for the MuJoCo ph…|\n|[pytorch-a2c-ppo-acktr-gail](https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail)|1.5k|PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region met…|\n|[Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese)|1.5k|【干货】史上最全的PyTorch学习资源汇总|\n|[deep-rl-tensorflow](https://github.com/carpedm20/deep-rl-tensorflow)|1.5k|TensorFlow implementation of Deep Reinforcement Learning papers|\n|[mkl-dnn](https://github.com/intel/mkl-dnn)|1.5k|Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)|\n|[automl-gs](https://github.com/minimaxir/automl-gs)|1.5k|Provide an input CSV and a target field to predict, generate a model + code to run it.|\n|[pytorch-summary](https://github.com/sksq96/pytorch-summary)|1.5k|Model summary in PyTorch similar to `model.summary()` in Keras|\n|[3D-ResNets-PyTorch](https://github.com/kenshohara/3D-ResNets-PyTorch)|1.5k|3D ResNets for Action Recognition (CVPR 2018)|\n|[chess-alpha-zero](https://github.com/Zeta36/chess-alpha-zero)|1.5k|Chess reinforcement learning by AlphaGo Zero methods.|\n|[keras-yolo2](https://github.com/experiencor/keras-yolo2)|1.5k|Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[texar](https://github.com/asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[XLearning](https://github.com/Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[DeepLearningForNLPInPytorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[tacotron](https://github.com/Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[fast-wavenet](https://github.com/tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[sequence_tagging](https://github.com/guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[BigGAN-PyTorch](https://github.com/ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[donkeycar](https://github.com/autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[quiver](https://github.com/keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[datasets](https://github.com/tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[edge-connect](https://github.com/knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[alpha-zero-general](https://github.com/suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[coach](https://github.com/NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[human-pose-estimation.pytorch](https://github.com/microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[GDLnotes](https://github.com/ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[mathAI](https://github.com/Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[zi2zi](https://github.com/kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[tensorflow-yolov3](https://github.com/YunYang1994/tensorflow-yolov3)|1.4k|🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset|\n|[TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[seldon-server](https://github.com/SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[gandissect](https://github.com/CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[tinyflow](https://github.com/tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[zh-NER-TF](https://github.com/Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[UNIT](https://github.com/mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers)|\n|[DeblurGAN](https://github.com/KupynOrest/DeblurGAN)|1.4k|Image Deblurring using Generative Adversarial Networks|\n|[NeuroNER](https://github.com/Franck-Dernoncourt/NeuroNER)|1.3k|Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.|\n|[tf_unet](https://github.com/jakeret/tf_unet)|1.3k|Generic U-Net Tensorflow implementation for image segmentation|\n|[torchsample](https://github.com/ncullen93/torchsample)|1.3k|High-Level Training, Data Augmentation, and Utilities for Pytorch|\n|[models](https://github.com/onnx/models)|1.3k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[CADL](https://github.com/pkmital/CADL)|1.3k|Course materials/Homework materials for the FREE MOOC course on \"Creative Applications of Deep Learning w/ Tensorflow…|\n|[CoreML-in-ARKit](https://github.com/hanleyweng/CoreML-in-ARKit)|1.3k|Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit…|\n|[DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[BerryNet](https://github.com/DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[pai](https://github.com/microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "1d2ea8e9f4d1814d81deccfcd68f6e9e64936212": {"t": 1785772717.9321845, "n": 44868, "h": "4412e26066f134d3", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2018.08.12\n\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow](https://github.com/tensorflow/tensorflow)|133k|An Open Source Machine Learning Framework for Everyone|\n|[models](https://github.com/tensorflow/models)|56.5k|Models and examples built with TensorFlow|\n|[keras](https://github.com/keras-team/keras)|43.4k|Deep Learning for humans|\n|[scikit-learn](https://github.com/scikit-learn/scikit-learn)|36.6k|scikit-learn: machine learning in Python|\n|[TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|33.4k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[pytorch](https://github.com/pytorch/pytorch)|30.8k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[caffe](https://github.com/BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[practicalAI](https://github.com/GokuMohandas/practicalAI)|19.5k|📚 A practical approach to machine learning.|\n|[incubator-mxnet](https://github.com/apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[bert](https://github.com/google-research/bert)|17.4k|TensorFlow code and pre-trained models for BERT|\n|[CNTK](https://github.com/microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[handson-ml](https://github.com/ageron/handson-ml)|16.3k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[fastai](https://github.com/fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.5k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.9k|PyTorch Tutorial for Deep Learning Researchers|\n|[homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|12.1k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[Virgilio](https://github.com/virgili0/Virgilio)|11.6k|Your new Mentor for Data Science E-Learning.|\n|[funNLP](https://github.com/fighting41love/funNLP)|11.5k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[deeplearning4j](https://github.com/eclipse/deeplearning4j)|11.1k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.8k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.3k|Image-to-Image Translation in PyTorch|\n|[LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[turicreate](https://github.com/apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[ChatterBot](https://github.com/gunthercox/ChatterBot)|8.8k|ChatterBot is a machine learning, conversational dialog engine for creating chat bots|\n|[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[tensor2tensor](https://github.com/tensorflow/tensor2tensor)|8.6k|Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.|\n|[caffe2](https://github.com/facebookarchive/caffe2)|8.5k|Caffe2 is a lightweight, modular, and scalable deep learning framework.|\n|[DeepCreamPy](https://github.com/deeppomf/DeepCreamPy)|8.3k|Decensoring Hentai with Deep Neural Networks|\n|[fast-style-transfer](https://github.com/lengstrom/fast-style-transfer)|8.2k|TensorFlow CNN for fast style transfer ⚡🖥🎨🖼|\n|[dopamine](https://github.com/google/dopamine)|8.2k|Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.|\n|[sonnet](https://github.com/deepmind/sonnet)|7.8k|TensorFlow-based neural network library|\n|[dlib](https://github.com/davisking/dlib)|7.7k|A toolkit for making real world machine learning and data analysis applications in C++|\n|[deep-learning-with-python-notebooks](https://github.com/fchollet/deep-learning-with-python-notebooks)|7.7k|Jupyter notebooks for the code samples of the book \"Deep Learning with Python\"|\n|[MLAlgorithms](https://github.com/rushter/MLAlgorithms)|7.6k|Minimal and clean examples of machine learning algorithms implementations|\n|[stylegan](https://github.com/NVlabs/stylegan)|7.5k|StyleGAN - Official TensorFlow Implementation|\n|[TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials)|7.5k|TensorFlow Tutorials with YouTube Videos|\n|[DeOldify](https://github.com/jantic/DeOldify)|7.5k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[kubeflow](https://github.com/kubeflow/kubeflow)|7.3k|Machine Learning Toolkit for Kubernetes|\n|[php-ml](https://github.com/php-ai/php-ml)|7.3k|PHP-ML - Machine Learning library for PHP|\n|[horovod](https://github.com/horovod/horovod)|7.2k|Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.|\n|[pattern](https://github.com/clips/pattern)|7.1k|Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysi…|\n|[allennlp](https://github.com/allenai/allennlp)|6.9k|An open-source NLP research library, built on PyTorch.|\n|[flair](https://github.com/zalandoresearch/flair)|6.9k|A very simple framework for state-of-the-art Natural Language Processing (NLP)|\n|[pytorch-handbook](https://github.com/zergtant/pytorch-handbook)|6.7k|pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行|\n|[golearn](https://github.com/sjwhitworth/golearn)|6.7k|Machine Learning for Go|\n|[imgaug](https://github.com/aleju/imgaug)|6.7k|Image augmentation for machine learning experiments.|\n|[vid2vid](https://github.com/NVIDIA/vid2vid)|6.7k|Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.|\n|[face-api.js](https://github.com/justadudewhohacks/face-api.js)|6.6k|JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js|\n|[tutorials](https://github.com/MorvanZhou/tutorials)|6.6k|机器学习相关教程|\n|[onnx](https://github.com/onnx/onnx)|6.6k|Open Neural Network Exchange|\n|[mit-deep-learning-book-pdf](https://github.com/janishar/mit-deep-learning-book-pdf)|6.5k|MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville|\n|[vowpal_wabbit](https://github.com/VowpalWabbit/vowpal_wabbit)|6.5k|Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as onli…|\n|[ml-agents](https://github.com/Unity-Technologies/ml-agents)|6.5k|Unity Machine Learning Agents Toolkit|\n|[numpy-ml](https://github.com/ddbourgin/numpy-ml)|6.4k|Machine learning, in numpy|\n|[machinelearning](https://github.com/dotnet/machinelearning)|6.3k|ML.NET is an open source and cross-platform machine learning framework for .NET.|\n|[lime](https://github.com/marcotcr/lime)|6.3k|Lime: Explaining the predictions of any machine learning classifier|\n|[rasa](https://github.com/RasaHQ/rasa)|6.2k|💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, c…|\n|[maskrcnn-benchmark](https://github.com/facebookresearch/maskrcnn-benchmark)|6.2k|Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.|\n|[tpot](https://github.com/EpistasisLab/tpot)|6.1k|A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.|\n|[shap](https://github.com/slundberg/shap)|6.1k|A unified approach to explain the output of any machine learning model.|\n|[DCGAN-tensorflow](https://github.com/carpedm20/DCGAN-tensorflow)|6k|A tensorflow implementation of \"Deep Convolutional Generative Adversarial Networks\"|\n|[machine-learning-course](https://github.com/machinelearningmindset/machine-learning-course)|5.9k|💬 Machine Learning Course with Python. Refer to the course page for step-by-step explanations.|\n|[autokeras](https://github.com/keras-team/autokeras)|5.8k|Accessible AutoML for deep learning.|\n|[netron](https://github.com/lutzroeder/netron)|5.8k|Visualizer for neural network, deep learning and machine learning models|\n|[mmdetection](https://github.com/open-mmlab/mmdetection)|5.7k|Open MMLab Detection Toolbox and Benchmark|\n|[facets](https://github.com/PAIR-code/facets)|5.7k|Visualizations for machine learning datasets|\n|[ludwig](https://github.com/uber/ludwig)|5.6k|Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to…|\n|[Swift-AI](https://github.com/Swift-AI/Swift-AI)|5.6k|The Swift machine learning library.|\n|[DeepFaceLab](https://github.com/iperov/DeepFaceLab)|5.6k|DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. Includes prebuilt ready to work stan…|\n|[mit-deep-learning](https://github.com/lexfridman/mit-deep-learning)|5.6k|Tutorials, assignments, and competitions for MIT Deep Learning related courses.|\n|[pytorch-book](https://github.com/chenyuntc/pytorch-book)|5.5k|PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation|\n|[pyro](https://github.com/pyro-ppl/pyro)|5.5k|Deep universal probabilistic programming with Python and PyTorch|\n|[generative-models](https://github.com/wiseodd/generative-models)|5.4k|Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.|\n|[guess](https://github.com/guess-js/guess)|5.4k|Libraries & tools for enabling Machine Learning driven user-experiences on the web|\n|[tensorboardX](https://github.com/lanpa/tensorboardX)|5.4k|tensorboard for pytorch (and chainer, mxnet, numpy, ...)|\n|[tensorlayer](https://github.com/tensorlayer/tensorlayer)|5.4k|Deep Learning and Reinforcement Learning Library for Scientists|\n|[bullet3](https://github.com/bulletphysics/bullet3)|5.3k|Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics,|\n|[pytext](https://github.com/facebookresearch/pytext)|5.3k|A natural language modeling framework based on PyTorch|\n|[tensorflow_cookbook](https://github.com/nfmcclure/tensorflow_cookbook)|5.1k|Code for Tensorflow Machine Learning Cookbook|\n|[text_classification](https://github.com/brightmart/text_classification)|5.1k|all kinds of text classification models and more with deep learning|\n|[fairseq](https://github.com/pytorch/fairseq)|5k|Facebook AI Research Sequence-to-Sequence Toolkit written in Python.|\n|[deepo](https://github.com/ufoym/deepo)|5k|Set up deep learning environment in a single command line.|\n|[bert-as-service](https://github.com/hanxiao/bert-as-service)|5k|Mapping a variable-length sentence to a fixed-length vector using BERT model|\n|[darkflow](https://github.com/thtrieu/darkflow)|5k|Translate darknet to tensorflow. 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Pi|\n|[nlp-architect](https://github.com/NervanaSystems/nlp-architect)|2k|NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techn…|\n|[Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials](https://github.com/TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials)|2k|A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding in…|\n|[kcws](https://github.com/koth/kcws)|2k|Deep Learning Chinese Word Segment|\n|[EAST](https://github.com/argman/EAST)|1.9k|A tensorflow implementation of EAST text detector|\n|[Neural-Photo-Editor](https://github.com/ajbrock/Neural-Photo-Editor)|1.9k|A simple interface for editing natural photos with generative neural networks.|\n|[text-to-image](https://github.com/paarthneekhara/text-to-image)|1.9k|Text to image synthesis using thought vectors|\n|[ELF](https://github.com/facebookresearch/ELF)|1.9k|An 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The researcher's version of Keras|\n|[sru](https://github.com/taolei87/sru)|1.7k|Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)|\n|[Porcupine](https://github.com/Picovoice/Porcupine)|1.7k|On-device wake word detection powered by deep learning.|\n|[AlphaZero_Gomoku](https://github.com/junxiaosong/AlphaZero_Gomoku)|1.7k|An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)|\n|[MUNIT](https://github.com/NVlabs/MUNIT)|1.7k|Multimodal Unsupervised Image-to-Image Translation|\n|[mmlspark](https://github.com/Azure/mmlspark)|1.6k|Microsoft Machine Learning for Apache Spark|\n|[transparent_latent_gan](https://github.com/SummitKwan/transparent_latent_gan)|1.6k|Use supervised learning to illuminate the latent space of GAN for controlled generation and edit|\n|[Flux.jl](https://github.com/FluxML/Flux.jl)|1.6k|Relax! Flux is the ML library that doesn't make you tensor|\n|[deepschool.io](https://github.com/sachinruk/deepschool.io)|1.6k|Deep Learning tutorials in jupyter notebooks.|\n|[tacotron](https://github.com/keithito/tacotron)|1.6k|A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)|\n|[VoTT](https://github.com/microsoft/VoTT)|1.6k|Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.|\n|[euler](https://github.com/alibaba/euler)|1.6k|A distributed graph deep learning framework.|\n|[nnvm](https://github.com/dmlc/nnvm)|1.6k|move to https://github.com/dmlc/tvm/|\n|[dm_control](https://github.com/deepmind/dm_control)|1.6k|The DM Control Suite and Package is a tool for developing and testing reinforcement learning agents for the MuJoCo ph…|\n|[pytorch-a2c-ppo-acktr-gail](https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail)|1.5k|PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region met…|\n|[Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese)|1.5k|【干货】史上最全的PyTorch学习资源汇总|\n|[deep-rl-tensorflow](https://github.com/carpedm20/deep-rl-tensorflow)|1.5k|TensorFlow implementation of Deep Reinforcement Learning papers|\n|[mkl-dnn](https://github.com/intel/mkl-dnn)|1.5k|Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)|\n|[automl-gs](https://github.com/minimaxir/automl-gs)|1.5k|Provide an input CSV and a target field to predict, generate a model + code to run it.|\n|[pytorch-summary](https://github.com/sksq96/pytorch-summary)|1.5k|Model summary in PyTorch similar to `model.summary()` in Keras|\n|[3D-ResNets-PyTorch](https://github.com/kenshohara/3D-ResNets-PyTorch)|1.5k|3D ResNets for Action Recognition (CVPR 2018)|\n|[chess-alpha-zero](https://github.com/Zeta36/chess-alpha-zero)|1.5k|Chess reinforcement learning by AlphaGo Zero methods.|\n|[keras-yolo2](https://github.com/experiencor/keras-yolo2)|1.5k|Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[texar](https://github.com/asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[XLearning](https://github.com/Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[DeepLearningForNLPInPytorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[tacotron](https://github.com/Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[fast-wavenet](https://github.com/tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[sequence_tagging](https://github.com/guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[BigGAN-PyTorch](https://github.com/ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[donkeycar](https://github.com/autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[quiver](https://github.com/keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[datasets](https://github.com/tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[edge-connect](https://github.com/knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[alpha-zero-general](https://github.com/suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[coach](https://github.com/NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[human-pose-estimation.pytorch](https://github.com/microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[GDLnotes](https://github.com/ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[mathAI](https://github.com/Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[zi2zi](https://github.com/kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[tensorflow-yolov3](https://github.com/YunYang1994/tensorflow-yolov3)|1.4k|🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset|\n|[TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[seldon-server](https://github.com/SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[gandissect](https://github.com/CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[tinyflow](https://github.com/tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[zh-NER-TF](https://github.com/Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[UNIT](https://github.com/mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. 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This serves as a basic Template for an ARKit…|\n|[DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. 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A curated list of dedicated resources http://tensorflow.org|\n|[Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.5k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning)|13.3k|A curated list of awesome Deep Learning tutorials, projects and communities.|\n|[100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[Qix](https://github.com/ty4z2008/Qix)|12.8k|Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang|\n|[homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.8k|PyTorch Tutorial for Deep Learning Researchers|\n|[cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai)|12.5k|Essential Cheat Sheets for deep learning and machine learning researchers|\n|[predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[Virgilio](https://github.com/virgili0/Virgilio)|11.6k|Your new Mentor for Data Science E-Learning.|\n|[reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|11.5k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[funNLP](https://github.com/fighting41love/funNLP)|11.4k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[tensorflow-zh](https://github.com/jikexueyuanwiki/tensorflow-zh)|11.1k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[deeplearning4j](https://github.com/eclipse/deeplearning4j)|11.1k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.6k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning)|9.5k|Dive into Machine Learning with Python Jupyter notebook and scikit-learn!|\n|[neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials)|9.3k|machine learning and deep learning tutorials, articles and other resources|\n|[LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.2k|Image-to-Image Translation in PyTorch|\n|[nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning)|8.9k|VIP cheatsheets for Stanford's CS 229 Machine Learning|\n|[turicreate](https://github.com/apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[ChatterBot](https://github.com/gunthercox/ChatterBot)|8.7k|ChatterBot is a machine learning, conversational dialog engine for creating chat bots|\n|[state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems)|8.7k|This repository provides state of the art (SoTA) results for all machine learning problems. 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E.g. model conversion a…|\n|[sketch-code](https://github.com/ashnkumar/sketch-code)|3.9k|Keras model to generate HTML code from hand-drawn website mockups. 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machine learning in Go.|\n|[pythia](https://github.com/facebookresearch/pythia)|2.7k|A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)|\n|[MatchZoo](https://github.com/NTMC-Community/MatchZoo)|2.6k|Facilitating the design, comparison and sharing of deep text matching models.|\n|[ssd.pytorch](https://github.com/amdegroot/ssd.pytorch)|2.6k|A PyTorch Implementation of Single Shot MultiBox Detector|\n|[dgl](https://github.com/dmlc/dgl)|2.6k|Python package built to ease deep learning on graph, on top of existing DL frameworks.|\n|[deep-learning-keras-tensorflow](https://github.com/leriomaggio/deep-learning-keras-tensorflow)|2.6k|Introduction to Deep Neural Networks with Keras and Tensorflow|\n|[deep-learning-book](https://github.com/rasbt/deep-learning-book)|2.6k|Repository for \"Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in 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MakeGirlsMoe|\n|[machine-learning-yearning-cn](https://github.com/deeplearning-ai/machine-learning-yearning-cn)|2.4k|Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著|\n|[text-classification-cnn-rnn](https://github.com/gaussic/text-classification-cnn-rnn)|2.4k|CNN-RNN中文文本分类，基于TensorFlow|\n|[MachineLearning](https://github.com/allmachinelearning/MachineLearning)|2.4k|Machine learning resources|\n|[tensorforce](https://github.com/tensorforce/tensorforce)|2.4k|Tensorforce: a TensorFlow library for applied reinforcement learning|\n|[HyperLPR](https://github.com/zeusees/HyperLPR)|2.4k|基于深度学习高性能中文车牌识别 High Performance Chinese License Plate Recognition Framework.|\n|[tencent-ml-images](https://github.com/Tencent/tencent-ml-images)|2.4k|Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet|\n|[deepjazz](https://github.com/jisungk/deepjazz)|2.4k|Deep learning driven jazz generation using Keras & Theano!|\n|[benchmark_results](https://github.com/foolwood/benchmark_results)|2.4k|Visual Tracking Paper List|\n|[LSTM-Human-Activity-Recognition](https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition)|2.3k|Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo…|\n|[neural-style-tf](https://github.com/cysmith/neural-style-tf)|2.3k|TensorFlow (Python API) implementation of Neural Style|\n|[tensorwatch](https://github.com/microsoft/tensorwatch)|2.3k|Debugging, monitoring and visualization for Python Machine Learning and Data Science|\n|[stanfordnlp](https://github.com/stanfordnlp/stanfordnlp)|2.3k|Official Stanford NLP Python Library for Many Human Languages|\n|[VisualDL](https://github.com/PaddlePaddle/VisualDL)|2.3k|A platform to visualize the deep learning process and result.|\n|[d2l-en](https://github.com/d2l-ai/d2l-en)|2.3k|Dive into Deep Learning: an interactive deep learning book with code, math, and discussions|\n|[keras-vis](https://github.com/raghakot/keras-vis)|2.3k|Neural network visualization toolkit for keras|\n|[pyod](https://github.com/yzhao062/pyod)|2.3k|A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)|\n|[zhihu](https://github.com/NELSONZHAO/zhihu)|2.3k|This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Pyt…|\n|[text-detection-ctpn](https://github.com/eragonruan/text-detection-ctpn)|2.3k|text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network|\n|[training](https://github.com/cloud-annotations/training)|2.3k|🐝 Custom Object Detection and Classification Training|\n|[gluon-api](https://github.com/gluon-api/gluon-api)|2.3k|A clear, concise, simple yet powerful and efficient API for deep learning.|\n|[TensorFlow-and-DeepLearning-Tutorial](https://github.com/CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial)|2.3k|A TensorFlow & Deep Learning online course I taught in 2016|\n|[cvat](https://github.com/opencv/cvat)|2.3k|Powerful and efficient Computer Vision Annotation Tool (CVAT)|\n|[probability](https://github.com/tensorflow/probability)|2.3k|Probabilistic reasoning and statistical analysis in TensorFlow|\n|[reinforcement-learning](https://github.com/rlcode/reinforcement-learning)|2.3k|Minimal and Clean Reinforcement Learning Examples|\n|[deep-learning-model-convertor](https://github.com/ysh329/deep-learning-model-convertor)|2.2k|The convertor/conversion of deep learning models for different deep learning frameworks/softwares.|\n|[tensorflow-internals](https://github.com/horance-liu/tensorflow-internals)|2.2k|It is open source ebook about TensorFlow kernel and implementation mechanism.|\n|[darts](https://github.com/quark0/darts)|2.2k|Differentiable architecture search for convolutional and recurrent networks|\n|[luminoth](https://github.com/tryolabs/luminoth)|2.2k|Deep Learning toolkit for Computer Vision|\n|[OpenNMT](https://github.com/OpenNMT/OpenNMT)|2.2k|Open Source Neural Machine Translation in Torch|\n|[PocketFlow](https://github.com/Tencent/PocketFlow)|2.2k|An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.|\n|[deep-learning-v2-pytorch](https://github.com/udacity/deep-learning-v2-pytorch)|2.1k|Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegre…|\n|[DeepNLP-models-Pytorch](https://github.com/DSKSD/DeepNLP-models-Pytorch)|2.1k|Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)|\n|[jetson-inference](https://github.com/dusty-nv/jetson-inference)|2.1k|Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.|\n|[colorization](https://github.com/richzhang/colorization)|2.1k|Automatic colorization using deep neural networks. \"Colorful Image Colorization.\" In ECCV, 2016.|\n|[pytorch-semseg](https://github.com/meetshah1995/pytorch-semseg)|2.1k|Semantic Segmentation Architectures Implemented in PyTorch|\n|[ignite](https://github.com/pytorch/ignite)|2.1k|High-level library to help with training neural networks in PyTorch|\n|[pointnet](https://github.com/charlesq34/pointnet)|2.1k|PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation|\n|[polyaxon](https://github.com/polyaxon/polyaxon)|2.1k|A platform for reproducible and scalable machine learning and deep learning on kubernetes|\n|[Faster-RCNN_TF](https://github.com/smallcorgi/Faster-RCNN_TF)|2.1k|Faster-RCNN in Tensorflow|\n|[telegram-list](https://github.com/goq/telegram-list)|2k|List of telegram groups, channels & bots // Список интересных групп, каналов и ботов телеграма // Список чатов для пр…|\n|[3DDFA](https://github.com/cleardusk/3DDFA)|2k|The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.|\n|[interactive-deep-colorization](https://github.com/junyanz/interactive-deep-colorization)|2k|Deep learning software for colorizing black and white images with a few clicks.|\n|[tensorflow-on-raspberry-pi](https://github.com/samjabrahams/tensorflow-on-raspberry-pi)|2k|TensorFlow for Raspberry Pi|\n|[nlp-architect](https://github.com/NervanaSystems/nlp-architect)|2k|NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techn…|\n|[yolov3](https://github.com/ultralytics/yolov3)|2k|YOLOv3 in PyTorch > ONNX > CoreML > iOS|\n|[awesome-deeplearning-resources](https://github.com/endymecy/awesome-deeplearning-resources)|2k|Deep Learning and deep reinforcement learning research papers and some codes|\n|[kcws](https://github.com/koth/kcws)|2k|Deep Learning Chinese Word Segment|\n|[EAST](https://github.com/argman/EAST)|1.9k|A tensorflow implementation of EAST text detector|\n|[Neural-Photo-Editor](https://github.com/ajbrock/Neural-Photo-Editor)|1.9k|A simple interface for editing natural photos with generative neural networks.|\n|[text-to-image](https://github.com/paarthneekhara/text-to-image)|1.9k|Text to image synthesis using thought vectors|\n|[ELF](https://github.com/facebookresearch/ELF)|1.9k|An End-To-End, Lightweight and Flexible Platform for Game Research|\n|[rust](https://github.com/tensorflow/rust)|1.9k|Rust language bindings for TensorFlow|\n|[DeepRL-Agents](https://github.com/awjuliani/DeepRL-Agents)|1.9k|A set of Deep Reinforcement Learning Agents implemented in Tensorflow.|\n|[tensorflow-build](https://github.com/lakshayg/tensorflow-build)|1.9k|TensorFlow binaries supporting AVX, FMA, SSE|\n|[papers](https://github.com/aleju/papers)|1.9k|Summaries of machine learning papers|\n|[docs](https://github.com/tensorflow/docs)|1.9k|TensorFlow documentation|\n|[TensorFlow-Tutorials](https://github.com/golbin/TensorFlow-Tutorials)|1.9k|텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다|\n|[deepdetect](https://github.com/jolibrain/deepdetect)|1.9k|Deep Learning API and Server in C++11 support for Caffe, Caffe2, TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE|\n|[tensorflow-windows-wheel](https://github.com/fo40225/tensorflow-windows-wheel)|1.9k|Tensorflow prebuilt binary for Windows|\n|[Deep-Learning-for-Recommendation-Systems](https://github.com/robi56/Deep-Learning-for-Recommendation-Systems)|1.9k|This repository contains Deep Learning based articles , paper and repositories for Recommender Systems|\n|[srgan](https://github.com/tensorlayer/srgan)|1.9k|Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|\n|[tensorflow-speech-recognition](https://github.com/pannous/tensorflow-speech-recognition)|1.9k|🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks|\n|[decaNLP](https://github.com/salesforce/decaNLP)|1.9k|The Natural Language Decathlon: A Multitask Challenge for NLP|\n|[Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials](https://github.com/TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials)|1.9k|A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding in…|\n|[tangent](https://github.com/google/tangent)|1.9k|Source-to-Source Debuggable Derivatives in Pure Python|\n|[DeepCTR](https://github.com/shenweichen/DeepCTR)|1.8k|Easy-to-use,Modular and Extendible package of deep-learning based CTR models.|\n|[text](https://github.com/pytorch/text)|1.8k|Data loaders and abstractions for text and NLP|\n|[TensorFlow-Roadmap](https://github.com/astorfi/TensorFlow-Roadmap)|1.8k|📡 Organized & Useful Resources about Deep Learning with TensorFlow|\n|[Super-SloMo](https://github.com/avinashpaliwal/Super-SloMo)|1.8k|PyTorch implementation of Super SloMo by Jiang et al.|\n|[Deep_reinforcement_learning_Course](https://github.com/simoninithomas/Deep_reinforcement_learning_Course)|1.8k|Implementations from the free course Deep Reinforcement Learning with Tensorflow|\n|[spotlight](https://github.com/maciejkula/spotlight)|1.8k|Deep recommender models using PyTorch.|\n|[SiamMask](https://github.com/foolwood/SiamMask)|1.8k|[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach|\n|[seq2seq-couplet](https://github.com/wb14123/seq2seq-couplet)|1.8k|Play couplet with seq2seq model. 用深度学习对对联。|\n|[gluon-nlp](https://github.com/dmlc/gluon-nlp)|1.7k|NLP made easy|\n|[keras-attention-mechanism](https://github.com/philipperemy/keras-attention-mechanism)|1.7k|Attention mechanism Implementation for Keras.|\n|[awesome-production-machine-learning](https://github.com/EthicalML/awesome-production-machine-learning)|1.7k|A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning|\n|[Ad-papers](https://github.com/wzhe06/Ad-papers)|1.7k|Papers on Computational Advertising|\n|[deep-high-resolution-net.pytorch](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch)|1.7k|The project is an official implementation of our CVPR2019 paper \"Deep High-Resolution Representation Learning for Hum…|\n|[benchm-ml](https://github.com/szilard/benchm-ml)|1.7k|A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Pyt…|\n|[lingvo](https://github.com/tensorflow/lingvo)|1.7k|Lingvo|\n|[deepvariant](https://github.com/google/deepvariant)|1.7k|DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA…|\n|[byteps](https://github.com/bytedance/byteps)|1.7k|A high performance and general PS framework for distributed training|\n|[hub](https://github.com/tensorflow/hub)|1.7k|A library for transfer learning by reusing parts of TensorFlow models.|\n|[deepchem](https://github.com/deepchem/deepchem)|1.7k|Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology|\n|[zhusuan](https://github.com/thu-ml/zhusuan)|1.7k|A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow|\n|[Bender](https://github.com/xmartlabs/Bender)|1.7k|Easily craft fast Neural Networks on iOS! 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Flux is the ML library that doesn't make you tensor|\n|[deepschool.io](https://github.com/sachinruk/deepschool.io)|1.6k|Deep Learning tutorials in jupyter notebooks.|\n|[tacotron](https://github.com/keithito/tacotron)|1.6k|A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)|\n|[VoTT](https://github.com/microsoft/VoTT)|1.6k|Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.|\n|[euler](https://github.com/alibaba/euler)|1.6k|A distributed graph deep learning framework.|\n|[DALI](https://github.com/NVIDIA/DALI)|1.6k|A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep le…|\n|[DeepInterests](https://github.com/Honlan/DeepInterests)|1.6k|深度有趣|\n|[pytorch-lightning](https://github.com/williamFalcon/pytorch-lightning)|1.6k|Rapid research framework for PyTorch. The researcher's version of Keras|\n|[nnvm](https://github.com/dmlc/nnvm)|1.6k|move to https://github.com/dmlc/tvm/|\n|[dm_control](https://github.com/deepmind/dm_control)|1.6k|The DM Control Suite and Package is a tool for developing and testing reinforcement learning agents for the MuJoCo ph…|\n|[pytorch-a2c-ppo-acktr-gail](https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail)|1.5k|PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region met…|\n|[Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese)|1.5k|【干货】史上最全的PyTorch学习资源汇总|\n|[deep-rl-tensorflow](https://github.com/carpedm20/deep-rl-tensorflow)|1.5k|TensorFlow implementation of Deep Reinforcement Learning papers|\n|[mkl-dnn](https://github.com/intel/mkl-dnn)|1.5k|Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)|\n|[automl-gs](https://github.com/minimaxir/automl-gs)|1.5k|Provide an input CSV and a target field to predict, generate a model + code to run it.|\n|[pytorch-summary](https://github.com/sksq96/pytorch-summary)|1.5k|Model summary in PyTorch similar to `model.summary()` in Keras|\n|[3D-ResNets-PyTorch](https://github.com/kenshohara/3D-ResNets-PyTorch)|1.5k|3D ResNets for Action Recognition (CVPR 2018)|\n|[chess-alpha-zero](https://github.com/Zeta36/chess-alpha-zero)|1.5k|Chess reinforcement learning by AlphaGo Zero methods.|\n|[keras-yolo2](https://github.com/experiencor/keras-yolo2)|1.5k|Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[texar](https://github.com/asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[XLearning](https://github.com/Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[DeepLearningForNLPInPytorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[tacotron](https://github.com/Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[fast-wavenet](https://github.com/tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[sequence_tagging](https://github.com/guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[BigGAN-PyTorch](https://github.com/ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[donkeycar](https://github.com/autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[quiver](https://github.com/keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[datasets](https://github.com/tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[edge-connect](https://github.com/knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[alpha-zero-general](https://github.com/suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[coach](https://github.com/NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[human-pose-estimation.pytorch](https://github.com/microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[iOS_ML](https://github.com/alexsosn/iOS_ML)|1.4k|List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.|\n|[GDLnotes](https://github.com/ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[mathAI](https://github.com/Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[zi2zi](https://github.com/kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[AI-Job-Notes](https://github.com/amusi/AI-Job-Notes)|1.4k|AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）|\n|[tensorflow-yolov3](https://github.com/YunYang1994/tensorflow-yolov3)|1.4k|🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset|\n|[TensorKart](https://github.com/kevinhughes27/TensorKart)|1.4k|self-driving MarioKart with TensorFlow|\n|[TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[seldon-server](https://github.com/SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[turkce-yapay-zeka-kaynaklari](https://github.com/deeplearningturkiye/turkce-yapay-zeka-kaynaklari)|1.4k|Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.|\n|[gandissect](https://github.com/CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music)|1.4k|List of articles related to deep learning applied to music|\n|[tinyflow](https://github.com/tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[zh-NER-TF](https://github.com/Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[UNIT](https://github.com/mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers)|\n|[DeblurGAN](https://github.com/KupynOrest/DeblurGAN)|1.4k|Image Deblurring using Generative Adversarial Networks|\n|[NeuroNER](https://github.com/Franck-Dernoncourt/NeuroNER)|1.3k|Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.|\n|[torchsample](https://github.com/ncullen93/torchsample)|1.3k|High-Level Training, Data Augmentation, and Utilities for Pytorch|\n|[models](https://github.com/onnx/models)|1.3k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[CADL](https://github.com/pkmital/CADL)|1.3k|Course materials/Homework materials for the FREE MOOC course on \"Creative Applications of Deep Learning w/ Tensorflow…|\n|[tensorflow-1.4-billion-password-analysis](https://github.com/philipperemy/tensorflow-1.4-billion-password-analysis)|1.3k|Deep Learning model to analyze a large corpus of clear text passwords.|\n|[CoreML-in-ARKit](https://github.com/hanleyweng/CoreML-in-ARKit)|1.3k|Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit…|\n|[DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[BerryNet](https://github.com/DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[pai](https://github.com/microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "f40caca7f3194efa816c5a6ec3ff62bdb5a943fa": {"t": 1785772722.761397, "n": 57142, "h": "149d82a192444026", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2018.08.11\n\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow/tensorflow](https://github.com/tensorflow/tensorflow)|132k|An Open Source Machine Learning Framework for Everyone|\n|[tensorflow/models](https://github.com/tensorflow/models)|56.3k|Models and examples built with TensorFlow|\n|[keras-team/keras](https://github.com/keras-team/keras)|43.4k|Deep Learning for humans|\n|[josephmisiti/awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)|41.2k|A curated list of awesome Machine Learning frameworks, libraries and software.|\n|[scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn)|36.5k|scikit-learn: machine learning in Python|\n|[aymericdamien/TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|33.3k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[scutan90/DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions)|32.4k|深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续.....…|\n|[pytorch/pytorch](https://github.com/pytorch/pytorch)|30.7k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[BVLC/caffe](https://github.com/BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[exacity/deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese)|25.8k|Deep Learning Book Chinese Translation|\n|[imhuay/Algorithm_Interview_Notes-Chinese](https://github.com/imhuay/Algorithm_Interview_Notes-Chinese)|25.7k|2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记|\n|[floodsung/Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[xitu/gold-miner](https://github.com/xitu/gold-miner)|23.3k|🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：|\n|[ZuzooVn/machine-learning-for-software-engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)|22.3k|A complete daily plan for studying to become a machine learning engineer.|\n|[GokuMohandas/practicalAI](https://github.com/GokuMohandas/practicalAI)|19.5k|📚 A practical approach to machine learning.|\n|[terryum/awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers)|19.5k|The most cited deep learning papers|\n|[apache/incubator-mxnet](https://github.com/apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[google-research/bert](https://github.com/google-research/bert)|17.3k|TensorFlow code and pre-trained models for BERT|\n|[microsoft/CNTK](https://github.com/microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[donnemartin/data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[ageron/handson-ml](https://github.com/ageron/handson-ml)|16.2k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[fastai/fastai](https://github.com/fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[jtoy/awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)|14.8k|TensorFlow - A curated list of dedicated resources http://tensorflow.org|\n|[matterport/Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.4k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[ChristosChristofidis/awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning)|13.3k|A curated list of awesome Deep Learning tutorials, projects and communities.|\n|[MLEveryday/100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[machinelearningmindset/TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[ty4z2008/Qix](https://github.com/ty4z2008/Qix)|12.8k|Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang|\n|[trekhleb/homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[yunjey/pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.8k|PyTorch Tutorial for Deep Learning Researchers|\n|[kailashahirwar/cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai)|12.5k|Essential Cheat Sheets for deep learning and machine learning researchers|\n|[apache/predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[eriklindernoren/ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[virgili0/Virgilio](https://github.com/virgili0/Virgilio)|11.5k|Your new Mentor for Data Science E-Learning.|\n|[dennybritz/reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|11.5k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[fighting41love/funNLP](https://github.com/fighting41love/funNLP)|11.4k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[jikexueyuanwiki/tensorflow-zh](https://github.com/jikexueyuanwiki/tensorflow-zh)|11.1k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[eclipse/deeplearning4j](https://github.com/eclipse/deeplearning4j)|11k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[mozilla/DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[huggingface/pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.6k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[rasbt/python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[mnielsen/neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[karpathy/convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[NVIDIA/FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[pytorch/examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[PaddlePaddle/Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[hangtwenty/dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning)|9.5k|Dive into Machine Learning with Python Jupyter notebook and scikit-learn!|\n|[alexjc/neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[ujjwalkarn/Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials)|9.3k|machine learning and deep learning tutorials, articles and other resources|\n|[microsoft/LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn/tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[junyanz/pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.2k|Image-to-Image Translation in PyTorch|\n|[nndl/nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[rasbt/deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[afshinea/stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning)|8.9k|VIP cheatsheets for Stanford's CS 229 Machine Learning|\n|[apple/turicreate](https://github.com/apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[chiphuyen/stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[davidsandberg/facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[RedditSota/state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems)|8.7k|This repository provides state of the art (SoTA) results for all machine learning problems. 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Science|\n|[stanfordnlp/stanfordnlp](https://github.com/stanfordnlp/stanfordnlp)|2.3k|Official Stanford NLP Python Library for Many Human Languages|\n|[PaddlePaddle/VisualDL](https://github.com/PaddlePaddle/VisualDL)|2.3k|A platform to visualize the deep learning process and result.|\n|[d2l-ai/d2l-en](https://github.com/d2l-ai/d2l-en)|2.3k|Dive into Deep Learning: an interactive deep learning book with code, math, and discussions|\n|[raghakot/keras-vis](https://github.com/raghakot/keras-vis)|2.3k|Neural network visualization toolkit for keras|\n|[yzhao062/pyod](https://github.com/yzhao062/pyod)|2.3k|A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)|\n|[NELSONZHAO/zhihu](https://github.com/NELSONZHAO/zhihu)|2.3k|This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Pyt…|\n|[eragonruan/text-detection-ctpn](https://github.com/eragonruan/text-detection-ctpn)|2.3k|text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network|\n|[cloud-annotations/training](https://github.com/cloud-annotations/training)|2.3k|🐝 Custom Object Detection and Classification Training|\n|[gluon-api/gluon-api](https://github.com/gluon-api/gluon-api)|2.3k|A clear, concise, simple yet powerful and efficient API for deep learning.|\n|[CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial](https://github.com/CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial)|2.3k|A TensorFlow & Deep Learning online course I taught in 2016|\n|[opencv/cvat](https://github.com/opencv/cvat)|2.3k|Powerful and efficient Computer Vision Annotation Tool (CVAT)|\n|[tensorflow/probability](https://github.com/tensorflow/probability)|2.3k|Probabilistic reasoning and statistical analysis in TensorFlow|\n|[rlcode/reinforcement-learning](https://github.com/rlcode/reinforcement-learning)|2.3k|Minimal and Clean Reinforcement Learning Examples|\n|[ysh329/deep-learning-model-convertor](https://github.com/ysh329/deep-learning-model-convertor)|2.2k|The convertor/conversion of deep learning models for different deep learning frameworks/softwares.|\n|[horance-liu/tensorflow-internals](https://github.com/horance-liu/tensorflow-internals)|2.2k|It is open source ebook about TensorFlow kernel and implementation mechanism.|\n|[quark0/darts](https://github.com/quark0/darts)|2.2k|Differentiable architecture search for convolutional and recurrent networks|\n|[tryolabs/luminoth](https://github.com/tryolabs/luminoth)|2.2k|Deep Learning toolkit for Computer Vision|\n|[OpenNMT/OpenNMT](https://github.com/OpenNMT/OpenNMT)|2.2k|Open Source Neural Machine Translation in Torch|\n|[Tencent/PocketFlow](https://github.com/Tencent/PocketFlow)|2.2k|An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI 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Learning on Point Sets for 3D Classification and Segmentation|\n|[polyaxon/polyaxon](https://github.com/polyaxon/polyaxon)|2.1k|A platform for reproducible and scalable machine learning and deep learning on kubernetes|\n|[smallcorgi/Faster-RCNN_TF](https://github.com/smallcorgi/Faster-RCNN_TF)|2.1k|Faster-RCNN in Tensorflow|\n|[goq/telegram-list](https://github.com/goq/telegram-list)|2k|List of telegram groups, channels & bots // Список интересных групп, каналов и ботов телеграма // Список чатов для пр…|\n|[cleardusk/3DDFA](https://github.com/cleardusk/3DDFA)|2k|The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.|\n|[junyanz/interactive-deep-colorization](https://github.com/junyanz/interactive-deep-colorization)|2k|Deep learning software for colorizing black and white images with a few clicks.|\n|[samjabrahams/tensorflow-on-raspberry-pi](https://github.com/samjabrahams/tensorflow-on-raspberry-pi)|2k|TensorFlow for Raspberry Pi|\n|[NervanaSystems/nlp-architect](https://github.com/NervanaSystems/nlp-architect)|2k|NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techn…|\n|[pytorch/ignite](https://github.com/pytorch/ignite)|2k|High-level library to help with training neural networks in PyTorch|\n|[ultralytics/yolov3](https://github.com/ultralytics/yolov3)|2k|YOLOv3 in PyTorch > ONNX > CoreML > iOS|\n|[endymecy/awesome-deeplearning-resources](https://github.com/endymecy/awesome-deeplearning-resources)|2k|Deep Learning and deep reinforcement learning research papers and some codes|\n|[koth/kcws](https://github.com/koth/kcws)|2k|Deep Learning Chinese Word Segment|\n|[argman/EAST](https://github.com/argman/EAST)|1.9k|A tensorflow implementation of EAST text detector|\n|[ajbrock/Neural-Photo-Editor](https://github.com/ajbrock/Neural-Photo-Editor)|1.9k|A simple interface for editing natural photos with generative neural networks.|\n|[paarthneekhara/text-to-image](https://github.com/paarthneekhara/text-to-image)|1.9k|Text to image synthesis using thought vectors|\n|[facebookresearch/ELF](https://github.com/facebookresearch/ELF)|1.9k|An End-To-End, Lightweight and Flexible Platform for Game Research|\n|[tensorflow/rust](https://github.com/tensorflow/rust)|1.9k|Rust language bindings for TensorFlow|\n|[awjuliani/DeepRL-Agents](https://github.com/awjuliani/DeepRL-Agents)|1.9k|A set of Deep Reinforcement Learning Agents implemented in Tensorflow.|\n|[lakshayg/tensorflow-build](https://github.com/lakshayg/tensorflow-build)|1.9k|TensorFlow binaries supporting AVX, FMA, SSE|\n|[aleju/papers](https://github.com/aleju/papers)|1.9k|Summaries of machine learning papers|\n|[golbin/TensorFlow-Tutorials](https://github.com/golbin/TensorFlow-Tutorials)|1.9k|텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다|\n|[jolibrain/deepdetect](https://github.com/jolibrain/deepdetect)|1.9k|Deep Learning API and Server in C++11 support for Caffe, Caffe2, TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE|\n|[fo40225/tensorflow-windows-wheel](https://github.com/fo40225/tensorflow-windows-wheel)|1.9k|Tensorflow prebuilt binary for Windows|\n|[robi56/Deep-Learning-for-Recommendation-Systems](https://github.com/robi56/Deep-Learning-for-Recommendation-Systems)|1.9k|This repository contains Deep Learning based articles , paper and repositories for Recommender Systems|\n|[tensorlayer/srgan](https://github.com/tensorlayer/srgan)|1.9k|Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|\n|[pannous/tensorflow-speech-recognition](https://github.com/pannous/tensorflow-speech-recognition)|1.9k|🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks|\n|[salesforce/decaNLP](https://github.com/salesforce/decaNLP)|1.9k|The Natural Language Decathlon: A Multitask Challenge for 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awesome open source libraries to deploy, monitor, version and scale your machine learning|\n|[wzhe06/Ad-papers](https://github.com/wzhe06/Ad-papers)|1.7k|Papers on Computational Advertising|\n|[szilard/benchm-ml](https://github.com/szilard/benchm-ml)|1.7k|A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Pyt…|\n|[tensorflow/lingvo](https://github.com/tensorflow/lingvo)|1.7k|Lingvo|\n|[google/deepvariant](https://github.com/google/deepvariant)|1.7k|DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA…|\n|[bytedance/byteps](https://github.com/bytedance/byteps)|1.7k|A high performance and general PS framework for distributed training|\n|[tensorflow/hub](https://github.com/tensorflow/hub)|1.7k|A library for transfer learning by reusing parts of TensorFlow models.|\n|[deepchem/deepchem](https://github.com/deepchem/deepchem)|1.7k|Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology|\n|[thu-ml/zhusuan](https://github.com/thu-ml/zhusuan)|1.7k|A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow|\n|[xmartlabs/Bender](https://github.com/xmartlabs/Bender)|1.7k|Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.|\n|[tobegit3hub/tensorflow_template_application](https://github.com/tobegit3hub/tensorflow_template_application)|1.7k|TensorFlow template application for deep learning|\n|[MrNothing/AI-Blocks](https://github.com/MrNothing/AI-Blocks)|1.7k|A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!|\n|[GauravBh1010tt/DeepLearn](https://github.com/GauravBh1010tt/DeepLearn)|1.7k|Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.|\n|[nl8590687/ASRT_SpeechRecognition](https://github.com/nl8590687/ASRT_SpeechRecognition)|1.7k|A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统|\n|[GeorgeSeif/Semantic-Segmentation-Suite](https://github.com/GeorgeSeif/Semantic-Segmentation-Suite)|1.7k|Semantic Segmentation Suite in TensorFlow. 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Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[asyml/texar](https://github.com/asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[Qihoo360/XLearning](https://github.com/Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[rguthrie3/DeepLearningForNLPInPytorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[Kyubyong/tacotron](https://github.com/Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[tomlepaine/fast-wavenet](https://github.com/tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[erhwenkuo/deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[guillaumegenthial/sequence_tagging](https://github.com/guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[williamFalcon/pytorch-lightning](https://github.com/williamFalcon/pytorch-lightning)|1.5k|Rapid research framework for PyTorch. The researcher's version of Keras|\n|[ajbrock/BigGAN-PyTorch](https://github.com/ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[autorope/donkeycar](https://github.com/autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[keplr-io/quiver](https://github.com/keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[tensorflow/datasets](https://github.com/tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[knazeri/edge-connect](https://github.com/knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[suragnair/alpha-zero-general](https://github.com/suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[NervanaSystems/coach](https://github.com/NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[microsoft/AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[microsoft/human-pose-estimation.pytorch](https://github.com/microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[alexsosn/iOS_ML](https://github.com/alexsosn/iOS_ML)|1.4k|List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.|\n|[ahangchen/GDLnotes](https://github.com/ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[Roujack/mathAI](https://github.com/Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[bfortuner/ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[kaonashi-tyc/zi2zi](https://github.com/kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[amusi/AI-Job-Notes](https://github.com/amusi/AI-Job-Notes)|1.4k|AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）|\n|[kevinhughes27/TensorKart](https://github.com/kevinhughes27/TensorKart)|1.4k|self-driving MarioKart with TensorFlow|\n|[dragen1860/TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[SeldonIO/seldon-server](https://github.com/SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[deeplearningturkiye/turkce-yapay-zeka-kaynaklari](https://github.com/deeplearningturkiye/turkce-yapay-zeka-kaynaklari)|1.4k|Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.|\n|[CSAILVision/gandissect](https://github.com/CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[ybayle/awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music)|1.4k|List of articles related to deep learning applied to music|\n|[tqchen/tinyflow](https://github.com/tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[Determined22/zh-NER-TF](https://github.com/Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[mingyuliutw/UNIT](https://github.com/mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[PetrochukM/PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. 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This serves as a basic Template for an ARKit…|\n|[NVIDIA/DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[RiweiChen/DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[DT42/BerryNet](https://github.com/DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[microsoft/pai](https://github.com/microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "628930f940e10111293d34a6880138da1018659b": {"t": 1785772724.4167976, "n": 57141, "h": "0bb481d5a3af00f7", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2018.08.11\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[tensorflow/tensorflow](https://github.com/tensorflow/tensorflow)|132k|An Open Source Machine Learning Framework for Everyone|\n|[tensorflow/models](https://github.com/tensorflow/models)|56.3k|Models and examples built with TensorFlow|\n|[keras-team/keras](https://github.com/keras-team/keras)|43.4k|Deep Learning for humans|\n|[josephmisiti/awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)|41.2k|A curated list of awesome Machine Learning frameworks, libraries and software.|\n|[scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn)|36.5k|scikit-learn: machine learning in Python|\n|[aymericdamien/TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples)|33.3k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[scutan90/DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions)|32.4k|深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续.....…|\n|[pytorch/pytorch](https://github.com/pytorch/pytorch)|30.7k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[BVLC/caffe](https://github.com/BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[exacity/deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese)|25.8k|Deep Learning Book Chinese Translation|\n|[imhuay/Algorithm_Interview_Notes-Chinese](https://github.com/imhuay/Algorithm_Interview_Notes-Chinese)|25.7k|2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记|\n|[floodsung/Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[xitu/gold-miner](https://github.com/xitu/gold-miner)|23.3k|🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：|\n|[ZuzooVn/machine-learning-for-software-engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers)|22.3k|A complete daily plan for studying to become a machine learning engineer.|\n|[GokuMohandas/practicalAI](https://github.com/GokuMohandas/practicalAI)|19.5k|📚 A practical approach to machine learning.|\n|[terryum/awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers)|19.5k|The most cited deep learning papers|\n|[apache/incubator-mxnet](https://github.com/apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[google-research/bert](https://github.com/google-research/bert)|17.3k|TensorFlow code and pre-trained models for BERT|\n|[microsoft/CNTK](https://github.com/microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[donnemartin/data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[ageron/handson-ml](https://github.com/ageron/handson-ml)|16.2k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[fastai/fastai](https://github.com/fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[jtoy/awesome-tensorflow](https://github.com/jtoy/awesome-tensorflow)|14.8k|TensorFlow - A curated list of dedicated resources http://tensorflow.org|\n|[matterport/Mask_RCNN](https://github.com/matterport/Mask_RCNN)|13.4k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[ChristosChristofidis/awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning)|13.3k|A curated list of awesome Deep Learning tutorials, projects and communities.|\n|[MLEveryday/100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[machinelearningmindset/TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[ty4z2008/Qix](https://github.com/ty4z2008/Qix)|12.8k|Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang|\n|[trekhleb/homemade-machine-learning](https://github.com/trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[yunjey/pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial)|12.8k|PyTorch Tutorial for Deep Learning Researchers|\n|[kailashahirwar/cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai)|12.5k|Essential Cheat Sheets for deep learning and machine learning researchers|\n|[apache/predictionio](https://github.com/apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[eriklindernoren/ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[virgili0/Virgilio](https://github.com/virgili0/Virgilio)|11.5k|Your new Mentor for Data Science E-Learning.|\n|[dennybritz/reinforcement-learning](https://github.com/dennybritz/reinforcement-learning)|11.5k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[fighting41love/funNLP](https://github.com/fighting41love/funNLP)|11.4k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[jikexueyuanwiki/tensorflow-zh](https://github.com/jikexueyuanwiki/tensorflow-zh)|11.1k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[eclipse/deeplearning4j](https://github.com/eclipse/deeplearning4j)|11k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[mozilla/DeepSpeech](https://github.com/mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[huggingface/pytorch-transformers](https://github.com/huggingface/pytorch-transformers)|10.6k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[rasbt/python-machine-learning-book](https://github.com/rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[mnielsen/neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[karpathy/convnetjs](https://github.com/karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[NVIDIA/FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[pytorch/examples](https://github.com/pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[PaddlePaddle/Paddle](https://github.com/PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[hangtwenty/dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning)|9.5k|Dive into Machine Learning with Python Jupyter notebook and scikit-learn!|\n|[alexjc/neural-enhance](https://github.com/alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[ujjwalkarn/Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials)|9.3k|machine learning and deep learning tutorials, articles and other resources|\n|[microsoft/LightGBM](https://github.com/microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[tflearn/tflearn](https://github.com/tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[junyanz/pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix)|9.2k|Image-to-Image Translation in PyTorch|\n|[nndl/nndl.github.io](https://github.com/nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[rasbt/deeplearning-models](https://github.com/rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[afshinea/stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning)|8.9k|VIP cheatsheets for Stanford's CS 229 Machine Learning|\n|[apple/turicreate](https://github.com/apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[chiphuyen/stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[davidsandberg/facenet](https://github.com/davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[RedditSota/state-of-the-art-result-for-machine-learning-problems](https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems)|8.7k|This repository provides state of the art (SoTA) results for all machine learning problems. 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Science|\n|[stanfordnlp/stanfordnlp](https://github.com/stanfordnlp/stanfordnlp)|2.3k|Official Stanford NLP Python Library for Many Human Languages|\n|[PaddlePaddle/VisualDL](https://github.com/PaddlePaddle/VisualDL)|2.3k|A platform to visualize the deep learning process and result.|\n|[d2l-ai/d2l-en](https://github.com/d2l-ai/d2l-en)|2.3k|Dive into Deep Learning: an interactive deep learning book with code, math, and discussions|\n|[raghakot/keras-vis](https://github.com/raghakot/keras-vis)|2.3k|Neural network visualization toolkit for keras|\n|[yzhao062/pyod](https://github.com/yzhao062/pyod)|2.3k|A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)|\n|[NELSONZHAO/zhihu](https://github.com/NELSONZHAO/zhihu)|2.3k|This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Pyt…|\n|[eragonruan/text-detection-ctpn](https://github.com/eragonruan/text-detection-ctpn)|2.3k|text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network|\n|[cloud-annotations/training](https://github.com/cloud-annotations/training)|2.3k|🐝 Custom Object Detection and Classification Training|\n|[gluon-api/gluon-api](https://github.com/gluon-api/gluon-api)|2.3k|A clear, concise, simple yet powerful and efficient API for deep learning.|\n|[CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial](https://github.com/CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial)|2.3k|A TensorFlow & Deep Learning online course I taught in 2016|\n|[opencv/cvat](https://github.com/opencv/cvat)|2.3k|Powerful and efficient Computer Vision Annotation Tool (CVAT)|\n|[tensorflow/probability](https://github.com/tensorflow/probability)|2.3k|Probabilistic reasoning and statistical analysis in TensorFlow|\n|[rlcode/reinforcement-learning](https://github.com/rlcode/reinforcement-learning)|2.3k|Minimal and Clean Reinforcement Learning Examples|\n|[ysh329/deep-learning-model-convertor](https://github.com/ysh329/deep-learning-model-convertor)|2.2k|The convertor/conversion of deep learning models for different deep learning frameworks/softwares.|\n|[horance-liu/tensorflow-internals](https://github.com/horance-liu/tensorflow-internals)|2.2k|It is open source ebook about TensorFlow kernel and implementation mechanism.|\n|[quark0/darts](https://github.com/quark0/darts)|2.2k|Differentiable architecture search for convolutional and recurrent networks|\n|[tryolabs/luminoth](https://github.com/tryolabs/luminoth)|2.2k|Deep Learning toolkit for Computer Vision|\n|[OpenNMT/OpenNMT](https://github.com/OpenNMT/OpenNMT)|2.2k|Open Source Neural Machine Translation in Torch|\n|[Tencent/PocketFlow](https://github.com/Tencent/PocketFlow)|2.2k|An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI 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Learning on Point Sets for 3D Classification and Segmentation|\n|[polyaxon/polyaxon](https://github.com/polyaxon/polyaxon)|2.1k|A platform for reproducible and scalable machine learning and deep learning on kubernetes|\n|[smallcorgi/Faster-RCNN_TF](https://github.com/smallcorgi/Faster-RCNN_TF)|2.1k|Faster-RCNN in Tensorflow|\n|[goq/telegram-list](https://github.com/goq/telegram-list)|2k|List of telegram groups, channels & bots // Список интересных групп, каналов и ботов телеграма // Список чатов для пр…|\n|[cleardusk/3DDFA](https://github.com/cleardusk/3DDFA)|2k|The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.|\n|[junyanz/interactive-deep-colorization](https://github.com/junyanz/interactive-deep-colorization)|2k|Deep learning software for colorizing black and white images with a few clicks.|\n|[samjabrahams/tensorflow-on-raspberry-pi](https://github.com/samjabrahams/tensorflow-on-raspberry-pi)|2k|TensorFlow for Raspberry Pi|\n|[NervanaSystems/nlp-architect](https://github.com/NervanaSystems/nlp-architect)|2k|NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techn…|\n|[pytorch/ignite](https://github.com/pytorch/ignite)|2k|High-level library to help with training neural networks in PyTorch|\n|[ultralytics/yolov3](https://github.com/ultralytics/yolov3)|2k|YOLOv3 in PyTorch > ONNX > CoreML > iOS|\n|[endymecy/awesome-deeplearning-resources](https://github.com/endymecy/awesome-deeplearning-resources)|2k|Deep Learning and deep reinforcement learning research papers and some codes|\n|[koth/kcws](https://github.com/koth/kcws)|2k|Deep Learning Chinese Word Segment|\n|[argman/EAST](https://github.com/argman/EAST)|1.9k|A tensorflow implementation of EAST text detector|\n|[ajbrock/Neural-Photo-Editor](https://github.com/ajbrock/Neural-Photo-Editor)|1.9k|A simple interface for editing natural photos with generative neural networks.|\n|[paarthneekhara/text-to-image](https://github.com/paarthneekhara/text-to-image)|1.9k|Text to image synthesis using thought vectors|\n|[facebookresearch/ELF](https://github.com/facebookresearch/ELF)|1.9k|An End-To-End, Lightweight and Flexible Platform for Game Research|\n|[tensorflow/rust](https://github.com/tensorflow/rust)|1.9k|Rust language bindings for TensorFlow|\n|[awjuliani/DeepRL-Agents](https://github.com/awjuliani/DeepRL-Agents)|1.9k|A set of Deep Reinforcement Learning Agents implemented in Tensorflow.|\n|[lakshayg/tensorflow-build](https://github.com/lakshayg/tensorflow-build)|1.9k|TensorFlow binaries supporting AVX, FMA, SSE|\n|[aleju/papers](https://github.com/aleju/papers)|1.9k|Summaries of machine learning papers|\n|[golbin/TensorFlow-Tutorials](https://github.com/golbin/TensorFlow-Tutorials)|1.9k|텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다|\n|[jolibrain/deepdetect](https://github.com/jolibrain/deepdetect)|1.9k|Deep Learning API and Server in C++11 support for Caffe, Caffe2, TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE|\n|[fo40225/tensorflow-windows-wheel](https://github.com/fo40225/tensorflow-windows-wheel)|1.9k|Tensorflow prebuilt binary for Windows|\n|[robi56/Deep-Learning-for-Recommendation-Systems](https://github.com/robi56/Deep-Learning-for-Recommendation-Systems)|1.9k|This repository contains Deep Learning based articles , paper and repositories for Recommender Systems|\n|[tensorlayer/srgan](https://github.com/tensorlayer/srgan)|1.9k|Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|\n|[pannous/tensorflow-speech-recognition](https://github.com/pannous/tensorflow-speech-recognition)|1.9k|🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks|\n|[salesforce/decaNLP](https://github.com/salesforce/decaNLP)|1.9k|The Natural Language Decathlon: A Multitask Challenge for 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awesome open source libraries to deploy, monitor, version and scale your machine learning|\n|[wzhe06/Ad-papers](https://github.com/wzhe06/Ad-papers)|1.7k|Papers on Computational Advertising|\n|[szilard/benchm-ml](https://github.com/szilard/benchm-ml)|1.7k|A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Pyt…|\n|[tensorflow/lingvo](https://github.com/tensorflow/lingvo)|1.7k|Lingvo|\n|[google/deepvariant](https://github.com/google/deepvariant)|1.7k|DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA…|\n|[bytedance/byteps](https://github.com/bytedance/byteps)|1.7k|A high performance and general PS framework for distributed training|\n|[tensorflow/hub](https://github.com/tensorflow/hub)|1.7k|A library for transfer learning by reusing parts of TensorFlow models.|\n|[deepchem/deepchem](https://github.com/deepchem/deepchem)|1.7k|Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology|\n|[thu-ml/zhusuan](https://github.com/thu-ml/zhusuan)|1.7k|A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow|\n|[xmartlabs/Bender](https://github.com/xmartlabs/Bender)|1.7k|Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.|\n|[tobegit3hub/tensorflow_template_application](https://github.com/tobegit3hub/tensorflow_template_application)|1.7k|TensorFlow template application for deep learning|\n|[MrNothing/AI-Blocks](https://github.com/MrNothing/AI-Blocks)|1.7k|A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!|\n|[GauravBh1010tt/DeepLearn](https://github.com/GauravBh1010tt/DeepLearn)|1.7k|Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.|\n|[nl8590687/ASRT_SpeechRecognition](https://github.com/nl8590687/ASRT_SpeechRecognition)|1.7k|A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统|\n|[GeorgeSeif/Semantic-Segmentation-Suite](https://github.com/GeorgeSeif/Semantic-Segmentation-Suite)|1.7k|Semantic Segmentation Suite in TensorFlow. 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Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[asyml/texar](https://github.com/asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[Qihoo360/XLearning](https://github.com/Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[rguthrie3/DeepLearningForNLPInPytorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[Kyubyong/tacotron](https://github.com/Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[tomlepaine/fast-wavenet](https://github.com/tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[erhwenkuo/deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[guillaumegenthial/sequence_tagging](https://github.com/guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[williamFalcon/pytorch-lightning](https://github.com/williamFalcon/pytorch-lightning)|1.5k|Rapid research framework for PyTorch. The researcher's version of Keras|\n|[ajbrock/BigGAN-PyTorch](https://github.com/ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[autorope/donkeycar](https://github.com/autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[keplr-io/quiver](https://github.com/keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[tensorflow/datasets](https://github.com/tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[knazeri/edge-connect](https://github.com/knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[suragnair/alpha-zero-general](https://github.com/suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[NervanaSystems/coach](https://github.com/NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[microsoft/AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[microsoft/human-pose-estimation.pytorch](https://github.com/microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[alexsosn/iOS_ML](https://github.com/alexsosn/iOS_ML)|1.4k|List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.|\n|[ahangchen/GDLnotes](https://github.com/ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[Roujack/mathAI](https://github.com/Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[bfortuner/ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[kaonashi-tyc/zi2zi](https://github.com/kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[amusi/AI-Job-Notes](https://github.com/amusi/AI-Job-Notes)|1.4k|AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）|\n|[kevinhughes27/TensorKart](https://github.com/kevinhughes27/TensorKart)|1.4k|self-driving MarioKart with TensorFlow|\n|[dragen1860/TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[SeldonIO/seldon-server](https://github.com/SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[deeplearningturkiye/turkce-yapay-zeka-kaynaklari](https://github.com/deeplearningturkiye/turkce-yapay-zeka-kaynaklari)|1.4k|Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.|\n|[CSAILVision/gandissect](https://github.com/CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[ybayle/awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music)|1.4k|List of articles related to deep learning applied to music|\n|[tqchen/tinyflow](https://github.com/tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[Determined22/zh-NER-TF](https://github.com/Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[mingyuliutw/UNIT](https://github.com/mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[PetrochukM/PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers)|\n|[KupynOrest/DeblurGAN](https://github.com/KupynOrest/DeblurGAN)|1.4k|Image Deblurring using Generative Adversarial Networks|\n|[Franck-Dernoncourt/NeuroNER](https://github.com/Franck-Dernoncourt/NeuroNER)|1.3k|Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.|\n|[ncullen93/torchsample](https://github.com/ncullen93/torchsample)|1.3k|High-Level Training, Data Augmentation, and Utilities for Pytorch|\n|[onnx/models](https://github.com/onnx/models)|1.3k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[pkmital/CADL](https://github.com/pkmital/CADL)|1.3k|Course materials/Homework materials for the FREE MOOC course on \"Creative Applications of Deep Learning w/ Tensorflow…|\n|[philipperemy/tensorflow-1.4-billion-password-analysis](https://github.com/philipperemy/tensorflow-1.4-billion-password-analysis)|1.3k|Deep Learning model to analyze a large corpus of clear text passwords.|\n|[YunYang1994/tensorflow-yolov3](https://github.com/YunYang1994/tensorflow-yolov3)|1.3k|🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset|\n|[hanleyweng/CoreML-in-ARKit](https://github.com/hanleyweng/CoreML-in-ARKit)|1.3k|Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit…|\n|[NVIDIA/DeepRecommender](https://github.com/NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[RiweiChen/DeepFace](https://github.com/RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[DT42/BerryNet](https://github.com/DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[microsoft/pai](https://github.com/microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "7c833a3ee62ee816ad0b67342b1f9d8bb082f2c3": {"t": 1785772725.934284, "n": 57142, "h": "d9f7ccc624de0daf", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2018.08.11\n\n| Project Name | Stars | Description |\n| ------- | ------ | ------ |\n|[https://github.com/tensorflow/tensorflow](tensorflow/tensorflow)|132k|An Open Source Machine Learning Framework for Everyone|\n|[https://github.com/tensorflow/models](tensorflow/models)|56.3k|Models and examples built with TensorFlow|\n|[https://github.com/keras-team/keras](keras-team/keras)|43.4k|Deep Learning for humans|\n|[https://github.com/josephmisiti/awesome-machine-learning](josephmisiti/awesome-machine-learning)|41.2k|A curated list of awesome Machine Learning frameworks, libraries and software.|\n|[https://github.com/scikit-learn/scikit-learn](scikit-learn/scikit-learn)|36.5k|scikit-learn: machine learning in Python|\n|[https://github.com/aymericdamien/TensorFlow-Examples](aymericdamien/TensorFlow-Examples)|33.3k|TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)|\n|[https://github.com/scutan90/DeepLearning-500-questions](scutan90/DeepLearning-500-questions)|32.4k|深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续.....…|\n|[https://github.com/pytorch/pytorch](pytorch/pytorch)|30.7k|Tensors and Dynamic neural networks in Python with strong GPU acceleration|\n|[https://github.com/BVLC/caffe](BVLC/caffe)|28.8k|Caffe: a fast open framework for deep learning.|\n|[https://github.com/exacity/deeplearningbook-chinese](exacity/deeplearningbook-chinese)|25.8k|Deep Learning Book Chinese Translation|\n|[https://github.com/imhuay/Algorithm_Interview_Notes-Chinese](imhuay/Algorithm_Interview_Notes-Chinese)|25.7k|2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记|\n|[https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap](floodsung/Deep-Learning-Papers-Reading-Roadmap)|23.7k|Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!|\n|[https://github.com/xitu/gold-miner](xitu/gold-miner)|23.3k|🥇掘金翻译计划，可能是世界最大最好的英译中技术社区，最懂读者和译者的翻译平台：|\n|[https://github.com/ZuzooVn/machine-learning-for-software-engineers](ZuzooVn/machine-learning-for-software-engineers)|22.3k|A complete daily plan for studying to become a machine learning engineer.|\n|[https://github.com/GokuMohandas/practicalAI](GokuMohandas/practicalAI)|19.5k|📚 A practical approach to machine learning.|\n|[https://github.com/terryum/awesome-deep-learning-papers](terryum/awesome-deep-learning-papers)|19.5k|The most cited deep learning papers|\n|[https://github.com/apache/incubator-mxnet](apache/incubator-mxnet)|17.5k|Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler;…|\n|[https://github.com/google-research/bert](google-research/bert)|17.3k|TensorFlow code and pre-trained models for BERT|\n|[https://github.com/microsoft/CNTK](microsoft/CNTK)|16.3k|Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit|\n|[https://github.com/donnemartin/data-science-ipython-notebooks](donnemartin/data-science-ipython-notebooks)|16.2k|Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spar…|\n|[https://github.com/ageron/handson-ml](ageron/handson-ml)|16.2k|A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python …|\n|[https://github.com/fastai/fastai](fastai/fastai)|15k|The fastai deep learning library, plus lessons and tutorials|\n|[https://github.com/jtoy/awesome-tensorflow](jtoy/awesome-tensorflow)|14.8k|TensorFlow - A curated list of dedicated resources http://tensorflow.org|\n|[https://github.com/matterport/Mask_RCNN](matterport/Mask_RCNN)|13.4k|Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow|\n|[https://github.com/ChristosChristofidis/awesome-deep-learning](ChristosChristofidis/awesome-deep-learning)|13.3k|A curated list of awesome Deep Learning tutorials, projects and communities.|\n|[https://github.com/MLEveryday/100-Days-Of-ML-Code](MLEveryday/100-Days-Of-ML-Code)|12.9k|100-Days-Of-ML-Code中文版|\n|[https://github.com/machinelearningmindset/TensorFlow-Course](machinelearningmindset/TensorFlow-Course)|12.9k|Simple and ready-to-use tutorials for TensorFlow|\n|[https://github.com/ty4z2008/Qix](ty4z2008/Qix)|12.8k|Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang|\n|[https://github.com/trekhleb/homemade-machine-learning](trekhleb/homemade-machine-learning)|12.8k|🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained|\n|[https://github.com/yunjey/pytorch-tutorial](yunjey/pytorch-tutorial)|12.8k|PyTorch Tutorial for Deep Learning Researchers|\n|[https://github.com/kailashahirwar/cheatsheets-ai](kailashahirwar/cheatsheets-ai)|12.5k|Essential Cheat Sheets for deep learning and machine learning researchers|\n|[https://github.com/apache/predictionio](apache/predictionio)|12k|PredictionIO, a machine learning server for developers and ML engineers.|\n|[https://github.com/eriklindernoren/ML-From-Scratch](eriklindernoren/ML-From-Scratch)|11.8k|Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focu…|\n|[https://github.com/virgili0/Virgilio](virgili0/Virgilio)|11.5k|Your new Mentor for Data Science E-Learning.|\n|[https://github.com/dennybritz/reinforcement-learning](dennybritz/reinforcement-learning)|11.5k|Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accom…|\n|[https://github.com/fighting41love/funNLP](fighting41love/funNLP)|11.4k|新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增…|\n|[https://github.com/jikexueyuanwiki/tensorflow-zh](jikexueyuanwiki/tensorflow-zh)|11.1k|谷歌全新开源人工智能系统TensorFlow官方文档中文版|\n|[https://github.com/eclipse/deeplearning4j](eclipse/deeplearning4j)|11k|Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark|\n|[https://github.com/mozilla/DeepSpeech](mozilla/DeepSpeech)|10.9k|A TensorFlow implementation of Baidu's DeepSpeech architecture|\n|[https://github.com/huggingface/pytorch-transformers](huggingface/pytorch-transformers)|10.6k|👾 A library of state-of-the-art pretrained models for Natural Language Processing (NLP)|\n|[https://github.com/rasbt/python-machine-learning-book](rasbt/python-machine-learning-book)|10.1k|The \"Python Machine Learning (1st edition)\" book code repository and info resource|\n|[https://github.com/mnielsen/neural-networks-and-deep-learning](mnielsen/neural-networks-and-deep-learning)|9.8k|Code samples for my book \"Neural Networks and Deep Learning\"|\n|[https://github.com/karpathy/convnetjs](karpathy/convnetjs)|9.8k|Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.|\n|[https://github.com/NVIDIA/FastPhotoStyle](NVIDIA/FastPhotoStyle)|9.8k|Style transfer, deep learning, feature transform|\n|[https://github.com/pytorch/examples](pytorch/examples)|9.7k|A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.|\n|[https://github.com/PaddlePaddle/Paddle](PaddlePaddle/Paddle)|9.6k|PArallel Distributed Deep LEarning （『飞桨』核心框架，高性能单机、分布式训练和跨平台部署）|\n|[https://github.com/hangtwenty/dive-into-machine-learning](hangtwenty/dive-into-machine-learning)|9.5k|Dive into Machine Learning with Python Jupyter notebook and scikit-learn!|\n|[https://github.com/alexjc/neural-enhance](alexjc/neural-enhance)|9.4k|Super Resolution for images using deep learning.|\n|[https://github.com/ujjwalkarn/Machine-Learning-Tutorials](ujjwalkarn/Machine-Learning-Tutorials)|9.3k|machine learning and deep learning tutorials, articles and other resources|\n|[https://github.com/microsoft/LightGBM](microsoft/LightGBM)|9.3k|A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tr…|\n|[https://github.com/tflearn/tflearn](tflearn/tflearn)|9.2k|Deep learning library featuring a higher-level API for TensorFlow.|\n|[https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix](junyanz/pytorch-CycleGAN-and-pix2pix)|9.2k|Image-to-Image Translation in PyTorch|\n|[https://github.com/nndl/nndl.github.io](nndl/nndl.github.io)|9.1k|《神经网络与深度学习》 Neural Network and Deep Learning|\n|[https://github.com/rasbt/deeplearning-models](rasbt/deeplearning-models)|9k|A collection of various deep learning architectures, models, and tips|\n|[https://github.com/afshinea/stanford-cs-229-machine-learning](afshinea/stanford-cs-229-machine-learning)|8.9k|VIP cheatsheets for Stanford's CS 229 Machine Learning|\n|[https://github.com/apple/turicreate](apple/turicreate)|8.9k|Turi Create simplifies the development of custom machine learning models.|\n|[https://github.com/chiphuyen/stanford-tensorflow-tutorials](chiphuyen/stanford-tensorflow-tutorials)|8.8k|This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.|\n|[https://github.com/davidsandberg/facenet](davidsandberg/facenet)|8.8k|Face recognition using Tensorflow|\n|[https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems](RedditSota/state-of-the-art-result-for-machine-learning-problems)|8.7k|This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep th…|\n|[https://github.com/gunthercox/ChatterBot](gunthercox/ChatterBot)|8.7k|ChatterBot is a machine learning, conversational dialog engine for creating chat bots|\n|[https://github.com/tensorflow/tensor2tensor](tensorflow/tensor2tensor)|8.5k|Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.|\n|[https://github.com/facebookarchive/caffe2](facebookarchive/caffe2)|8.5k|Caffe2 is a lightweight, modular, and scalable deep learning framework.|\n|[https://github.com/vahidk/EffectiveTensorflow](vahidk/EffectiveTensorflow)|8.4k|TensorFlow 1.x and 2.x tutorials and best practices.|\n|[https://github.com/kjw0612/awesome-deep-vision](kjw0612/awesome-deep-vision)|8.4k|A curated list of deep learning resources for computer vision|\n|[https://github.com/deeppomf/DeepCreamPy](deeppomf/DeepCreamPy)|8.3k|Decensoring Hentai with Deep Neural Networks|\n|[https://github.com/lengstrom/fast-style-transfer](lengstrom/fast-style-transfer)|8.2k|TensorFlow CNN for fast style transfer ⚡🖥🎨🖼|\n|[https://github.com/google/dopamine](google/dopamine)|8.2k|Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.|\n|[https://github.com/deepmind/sonnet](deepmind/sonnet)|7.8k|TensorFlow-based neural network library|\n|[https://github.com/davisking/dlib](davisking/dlib)|7.7k|A toolkit for making real world machine learning and data analysis applications in C++|\n|[https://github.com/fchollet/deep-learning-with-python-notebooks](fchollet/deep-learning-with-python-notebooks)|7.7k|Jupyter notebooks for the code samples of the book \"Deep Learning with Python\"|\n|[https://github.com/bharathgs/Awesome-pytorch-list](bharathgs/Awesome-pytorch-list)|7.6k|A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,t…|\n|[https://github.com/rushter/MLAlgorithms](rushter/MLAlgorithms)|7.6k|Minimal and clean examples of machine learning algorithms implementations|\n|[https://github.com/NVlabs/stylegan](NVlabs/stylegan)|7.5k|StyleGAN - Official TensorFlow Implementation|\n|[https://github.com/Hvass-Labs/TensorFlow-Tutorials](Hvass-Labs/TensorFlow-Tutorials)|7.5k|TensorFlow Tutorials with YouTube Videos|\n|[https://github.com/jantic/DeOldify](jantic/DeOldify)|7.4k|A Deep Learning based project for colorizing and restoring old images (and video!)|\n|[https://github.com/kubeflow/kubeflow](kubeflow/kubeflow)|7.3k|Machine Learning Toolkit for Kubernetes|\n|[https://github.com/php-ai/php-ml](php-ai/php-ml)|7.3k|PHP-ML - Machine Learning library for PHP|\n|[https://github.com/horovod/horovod](horovod/horovod)|7.2k|Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.|\n|[https://github.com/clips/pattern](clips/pattern)|7.1k|Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysi…|\n|[https://github.com/vdumoulin/conv_arithmetic](vdumoulin/conv_arithmetic)|7.1k|A technical report on convolution arithmetic in the context of deep learning|\n|[https://github.com/zalandoresearch/flair](zalandoresearch/flair)|6.9k|A very simple framework for state-of-the-art Natural Language Processing (NLP)|\n|[https://github.com/allenai/allennlp](allenai/allennlp)|6.8k|An open-source NLP research library, built on PyTorch.|\n|[https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months](llSourcell/Learn_Machine_Learning_in_3_Months)|6.7k|This is the code for \"Learn Machine Learning in 3 Months\" by Siraj Raval on Youtube|\n|[https://github.com/sjwhitworth/golearn](sjwhitworth/golearn)|6.7k|Machine Learning for Go|\n|[https://github.com/aleju/imgaug](aleju/imgaug)|6.7k|Image augmentation for machine learning experiments.|\n|[https://github.com/NVIDIA/vid2vid](NVIDIA/vid2vid)|6.7k|Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.|\n|[https://github.com/justadudewhohacks/face-api.js](justadudewhohacks/face-api.js)|6.6k|JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js|\n|[https://github.com/MorvanZhou/tutorials](MorvanZhou/tutorials)|6.6k|机器学习相关教程|\n|[https://github.com/zergtant/pytorch-handbook](zergtant/pytorch-handbook)|6.6k|pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行|\n|[https://github.com/onnx/onnx](onnx/onnx)|6.6k|Open Neural Network Exchange|\n|[https://github.com/janishar/mit-deep-learning-book-pdf](janishar/mit-deep-learning-book-pdf)|6.5k|MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville|\n|[https://github.com/VowpalWabbit/vowpal_wabbit](VowpalWabbit/vowpal_wabbit)|6.5k|Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as onli…|\n|[https://github.com/Unity-Technologies/ml-agents](Unity-Technologies/ml-agents)|6.5k|Unity Machine Learning Agents Toolkit|\n|[https://github.com/dotnet/machinelearning](dotnet/machinelearning)|6.3k|ML.NET is an open source and cross-platform machine learning framework for .NET.|\n|[https://github.com/marcotcr/lime](marcotcr/lime)|6.3k|Lime: Explaining the predictions of any machine learning classifier|\n|[https://github.com/ddbourgin/numpy-ml](ddbourgin/numpy-ml)|6.3k|Machine learning, in numpy|\n|[https://github.com/facebookresearch/maskrcnn-benchmark](facebookresearch/maskrcnn-benchmark)|6.2k|Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.|\n|[https://github.com/EpistasisLab/tpot](EpistasisLab/tpot)|6.1k|A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.|\n|[https://github.com/RasaHQ/rasa](RasaHQ/rasa)|6.1k|💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, c…|\n|[https://github.com/slundberg/shap](slundberg/shap)|6.1k|A unified approach to explain the output of any machine learning model.|\n|[https://github.com/carpedm20/DCGAN-tensorflow](carpedm20/DCGAN-tensorflow)|6k|A tensorflow implementation of \"Deep Convolutional Generative Adversarial Networks\"|\n|[https://github.com/kmario23/deep-learning-drizzle](kmario23/deep-learning-drizzle)|5.8k|Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from…|\n|[https://github.com/keras-team/autokeras](keras-team/autokeras)|5.8k|Accessible AutoML for deep learning.|\n|[https://github.com/nlintz/TensorFlow-Tutorials](nlintz/TensorFlow-Tutorials)|5.8k|Simple tutorials using Google's TensorFlow Framework|\n|[https://github.com/machinelearningmindset/machine-learning-course](machinelearningmindset/machine-learning-course)|5.8k|💬 Machine Learning Course with Python. Refer to the course page for step-by-step explanations.|\n|[https://github.com/hoya012/deep_learning_object_detection](hoya012/deep_learning_object_detection)|5.7k|A paper list of object detection using deep learning.|\n|[https://github.com/lutzroeder/netron](lutzroeder/netron)|5.7k|Visualizer for neural network, deep learning and machine learning models|\n|[https://github.com/open-mmlab/mmdetection](open-mmlab/mmdetection)|5.6k|Open MMLab Detection Toolbox and Benchmark|\n|[https://github.com/Swift-AI/Swift-AI](Swift-AI/Swift-AI)|5.6k|The Swift machine learning library.|\n|[https://github.com/lexfridman/mit-deep-learning](lexfridman/mit-deep-learning)|5.6k|Tutorials, assignments, and competitions for MIT Deep Learning related courses.|\n|[https://github.com/PAIR-code/facets](PAIR-code/facets)|5.6k|Visualizations for machine learning datasets|\n|[https://github.com/uber/ludwig](uber/ludwig)|5.5k|Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to…|\n|[https://github.com/iperov/DeepFaceLab](iperov/DeepFaceLab)|5.5k|DeepFaceLab is a tool that utilizes machine learning to replace faces in videos. 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Implements an image captioning architecture to dra…|\n|[https://github.com/jwyang/faster-rcnn.pytorch](jwyang/faster-rcnn.pytorch)|3.9k|A faster pytorch implementation of faster r-cnn|\n|[https://github.com/eriklindernoren/PyTorch-GAN](eriklindernoren/PyTorch-GAN)|3.8k|PyTorch implementations of Generative Adversarial Networks.|\n|[https://github.com/graykode/nlp-tutorial](graykode/nlp-tutorial)|3.8k|Natural Language Processing Tutorial for Deep Learning Researchers|\n|[https://github.com/NVIDIA/pix2pixHD](NVIDIA/pix2pixHD)|3.8k|Synthesizing and manipulating 2048x1024 images with conditional GANs|\n|[https://github.com/photoprism/photoprism](photoprism/photoprism)|3.8k|Personal Photo Management powered by Go and Google TensorFlow|\n|[https://github.com/ritchieng/the-incredible-pytorch](ritchieng/the-incredible-pytorch)|3.8k|The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.|\n|[https://github.com/PipelineAI/pipeline](PipelineAI/pipeline)|3.7k|PipelineAI: Real-Time Enterprise AI Platform|\n|[https://github.com/tensorflow/serving](tensorflow/serving)|3.7k|A flexible, high-performance serving system for machine learning models|\n|[https://github.com/OpenMined/PySyft](OpenMined/PySyft)|3.7k|A library for encrypted, privacy preserving deep learning|\n|[https://github.com/hunkim/DeepLearningZeroToAll](hunkim/DeepLearningZeroToAll)|3.6k|TensorFlow Basic Tutorial Labs|\n|[https://github.com/deepmind/graph_nets](deepmind/graph_nets)|3.6k|Build Graph Nets in Tensorflow|\n|[https://github.com/spro/practical-pytorch](spro/practical-pytorch)|3.5k|PyTorch tutorials demonstrating modern techniques with readable code|\n|[https://github.com/naturomics/CapsNet-Tensorflow](naturomics/CapsNet-Tensorflow)|3.5k|A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules|\n|[https://github.com/xitu/tensorflow-docs](xitu/tensorflow-docs)|3.5k|TensorFlow 最新官方文档中文版|\n|[https://github.com/MorvanZhou/PyTorch-Tutorial](MorvanZhou/PyTorch-Tutorial)|3.5k|Build your neural network easy and fast|\n|[https://github.com/deepmipt/DeepPavlov](deepmipt/DeepPavlov)|3.3k|An open source library for deep learning end-to-end dialog systems and chatbots.|\n|[https://github.com/MorvanZhou/Tensorflow-Tutorial](MorvanZhou/Tensorflow-Tutorial)|3.3k|Tensorflow tutorial from basic to hard|\n|[https://github.com/balancap/SSD-Tensorflow](balancap/SSD-Tensorflow)|3.3k|Single Shot MultiBox Detector in TensorFlow|\n|[https://github.com/yandexdataschool/Practical_RL](yandexdataschool/Practical_RL)|3.3k|A course in reinforcement learning in the wild|\n|[https://github.com/hwalsuklee/tensorflow-generative-model-collections](hwalsuklee/tensorflow-generative-model-collections)|3.3k|Collection of generative models in Tensorflow|\n|[https://github.com/OpenNMT/OpenNMT-py](OpenNMT/OpenNMT-py)|3.3k|Open Source Neural Machine Translation in PyTorch|\n|[https://github.com/yahoo/TensorFlowOnSpark](yahoo/TensorFlowOnSpark)|3.2k|TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.|\n|[https://github.com/apachecn/hands-on-ml-zh](apachecn/hands-on-ml-zh)|3.1k|📖 [译] Sklearn 与 TensorFlow 机器学习实用指南【版权问题，网站已下线！！】|\n|[https://github.com/cchen156/Learning-to-See-in-the-Dark](cchen156/Learning-to-See-in-the-Dark)|3.1k|Learning to See in the Dark. 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I've enjoyed ever…|\n|[https://github.com/AKSHAYUBHAT/DeepVideoAnalytics](AKSHAYUBHAT/DeepVideoAnalytics)|2.7k|A distributed visual search and visual data analytics platform.|\n|[https://github.com/taki0112/Tensorflow-Cookbook](taki0112/Tensorflow-Cookbook)|2.7k|Simple Tensorflow Cookbook for easy-to-use|\n|[https://github.com/hunkim/PyTorchZeroToAll](hunkim/PyTorchZeroToAll)|2.7k|Simple PyTorch Tutorials Zero to ALL!|\n|[https://github.com/andri27-ts/60_Days_RL_Challenge](andri27-ts/60_Days_RL_Challenge)|2.7k|Learn Deep Reinforcement Learning in Depth in 60 days|\n|[https://github.com/yusugomori/DeepLearning](yusugomori/DeepLearning)|2.7k|Deep Learning (Python, C, C++, Java, Scala, Go)|\n|[https://github.com/migueldeicaza/TensorFlowSharp](migueldeicaza/TensorFlowSharp)|2.7k|TensorFlow API for .NET languages|\n|[https://github.com/gorgonia/gorgonia](gorgonia/gorgonia)|2.7k|Gorgonia is a library that helps facilitate machine learning in 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Tensorflow|\n|[https://github.com/Conchylicultor/DeepQA](Conchylicultor/DeepQA)|2.5k|My tensorflow implementation of \"A neural conversational model\", a Deep learning based chatbot|\n|[https://github.com/makegirlsmoe/makegirlsmoe_web](makegirlsmoe/makegirlsmoe_web)|2.5k|Create Anime Characters with MakeGirlsMoe|\n|[https://github.com/deeplearning-ai/machine-learning-yearning-cn](deeplearning-ai/machine-learning-yearning-cn)|2.4k|Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著|\n|[https://github.com/gaussic/text-classification-cnn-rnn](gaussic/text-classification-cnn-rnn)|2.4k|CNN-RNN中文文本分类，基于TensorFlow|\n|[https://github.com/allmachinelearning/MachineLearning](allmachinelearning/MachineLearning)|2.4k|Machine learning resources|\n|[https://github.com/tensorforce/tensorforce](tensorforce/tensorforce)|2.4k|Tensorforce: a TensorFlow library for applied reinforcement learning|\n|[https://github.com/zeusees/HyperLPR](zeusees/HyperLPR)|2.4k|基于深度学习高性能中文车牌识别 High Performance Chinese License Plate Recognition Framework.|\n|[https://github.com/Tencent/tencent-ml-images](Tencent/tencent-ml-images)|2.4k|Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet|\n|[https://github.com/jisungk/deepjazz](jisungk/deepjazz)|2.4k|Deep learning driven jazz generation using Keras & Theano!|\n|[https://github.com/foolwood/benchmark_results](foolwood/benchmark_results)|2.4k|Visual Tracking Paper List|\n|[https://github.com/guillaume-chevalier/LSTM-Human-Activity-Recognition](guillaume-chevalier/LSTM-Human-Activity-Recognition)|2.3k|Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo…|\n|[https://github.com/cysmith/neural-style-tf](cysmith/neural-style-tf)|2.3k|TensorFlow (Python API) implementation of Neural Style|\n|[https://github.com/microsoft/tensorwatch](microsoft/tensorwatch)|2.3k|Debugging, monitoring and visualization for Python Machine Learning and Data Science|\n|[https://github.com/stanfordnlp/stanfordnlp](stanfordnlp/stanfordnlp)|2.3k|Official Stanford NLP Python Library for Many Human Languages|\n|[https://github.com/PaddlePaddle/VisualDL](PaddlePaddle/VisualDL)|2.3k|A platform to visualize the deep learning process and result.|\n|[https://github.com/d2l-ai/d2l-en](d2l-ai/d2l-en)|2.3k|Dive into Deep Learning: an interactive deep learning book with code, math, and discussions|\n|[https://github.com/raghakot/keras-vis](raghakot/keras-vis)|2.3k|Neural network visualization toolkit for keras|\n|[https://github.com/yzhao062/pyod](yzhao062/pyod)|2.3k|A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)|\n|[https://github.com/NELSONZHAO/zhihu](NELSONZHAO/zhihu)|2.3k|This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Pyt…|\n|[https://github.com/eragonruan/text-detection-ctpn](eragonruan/text-detection-ctpn)|2.3k|text detection mainly based on ctpn model in tensorflow, id card detect, connectionist text proposal network|\n|[https://github.com/cloud-annotations/training](cloud-annotations/training)|2.3k|🐝 Custom Object Detection and Classification Training|\n|[https://github.com/gluon-api/gluon-api](gluon-api/gluon-api)|2.3k|A clear, concise, simple yet powerful and efficient API for deep learning.|\n|[https://github.com/CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial](CreatCodeBuild/TensorFlow-and-DeepLearning-Tutorial)|2.3k|A TensorFlow & Deep Learning online course I taught in 2016|\n|[https://github.com/opencv/cvat](opencv/cvat)|2.3k|Powerful and efficient Computer Vision Annotation Tool (CVAT)|\n|[https://github.com/tensorflow/probability](tensorflow/probability)|2.3k|Probabilistic reasoning and statistical analysis in TensorFlow|\n|[https://github.com/rlcode/reinforcement-learning](rlcode/reinforcement-learning)|2.3k|Minimal and Clean Reinforcement Learning Examples|\n|[https://github.com/ysh329/deep-learning-model-convertor](ysh329/deep-learning-model-convertor)|2.2k|The convertor/conversion of deep learning models for different deep learning frameworks/softwares.|\n|[https://github.com/horance-liu/tensorflow-internals](horance-liu/tensorflow-internals)|2.2k|It is open source ebook about TensorFlow kernel and implementation mechanism.|\n|[https://github.com/quark0/darts](quark0/darts)|2.2k|Differentiable architecture search for convolutional and recurrent networks|\n|[https://github.com/tryolabs/luminoth](tryolabs/luminoth)|2.2k|Deep Learning toolkit for Computer Vision|\n|[https://github.com/OpenNMT/OpenNMT](OpenNMT/OpenNMT)|2.2k|Open Source Neural Machine Translation in Torch|\n|[https://github.com/Tencent/PocketFlow](Tencent/PocketFlow)|2.2k|An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.|\n|[https://github.com/udacity/deep-learning-v2-pytorch](udacity/deep-learning-v2-pytorch)|2.1k|Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegre…|\n|[https://github.com/DSKSD/DeepNLP-models-Pytorch](DSKSD/DeepNLP-models-Pytorch)|2.1k|Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)|\n|[https://github.com/dusty-nv/jetson-inference](dusty-nv/jetson-inference)|2.1k|Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.|\n|[https://github.com/richzhang/colorization](richzhang/colorization)|2.1k|Automatic colorization using deep neural networks. \"Colorful Image Colorization.\" In ECCV, 2016.|\n|[https://github.com/meetshah1995/pytorch-semseg](meetshah1995/pytorch-semseg)|2.1k|Semantic Segmentation Architectures Implemented in PyTorch|\n|[https://github.com/charlesq34/pointnet](charlesq34/pointnet)|2.1k|PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation|\n|[https://github.com/polyaxon/polyaxon](polyaxon/polyaxon)|2.1k|A platform for reproducible and scalable machine learning and deep learning on kubernetes|\n|[https://github.com/smallcorgi/Faster-RCNN_TF](smallcorgi/Faster-RCNN_TF)|2.1k|Faster-RCNN in Tensorflow|\n|[https://github.com/goq/telegram-list](goq/telegram-list)|2k|List of telegram groups, channels & bots // Список интересных групп, каналов и ботов телеграма // Список чатов для пр…|\n|[https://github.com/cleardusk/3DDFA](cleardusk/3DDFA)|2k|The PyTorch improved version of TPAMI 2017 paper: Face Alignment in Full Pose Range: A 3D Total Solution.|\n|[https://github.com/junyanz/interactive-deep-colorization](junyanz/interactive-deep-colorization)|2k|Deep learning software for colorizing black and white images with a few clicks.|\n|[https://github.com/samjabrahams/tensorflow-on-raspberry-pi](samjabrahams/tensorflow-on-raspberry-pi)|2k|TensorFlow for Raspberry Pi|\n|[https://github.com/NervanaSystems/nlp-architect](NervanaSystems/nlp-architect)|2k|NLP Architect by Intel AI Lab: A Python library for exploring the state-of-the-art deep learning topologies and techn…|\n|[https://github.com/pytorch/ignite](pytorch/ignite)|2k|High-level library to help with training neural networks in PyTorch|\n|[https://github.com/ultralytics/yolov3](ultralytics/yolov3)|2k|YOLOv3 in PyTorch > ONNX > CoreML > iOS|\n|[https://github.com/endymecy/awesome-deeplearning-resources](endymecy/awesome-deeplearning-resources)|2k|Deep Learning and deep reinforcement learning research papers and some codes|\n|[https://github.com/koth/kcws](koth/kcws)|2k|Deep Learning Chinese Word Segment|\n|[https://github.com/argman/EAST](argman/EAST)|1.9k|A tensorflow implementation of EAST text detector|\n|[https://github.com/ajbrock/Neural-Photo-Editor](ajbrock/Neural-Photo-Editor)|1.9k|A simple interface for editing natural photos with generative neural networks.|\n|[https://github.com/paarthneekhara/text-to-image](paarthneekhara/text-to-image)|1.9k|Text to image synthesis using thought vectors|\n|[https://github.com/facebookresearch/ELF](facebookresearch/ELF)|1.9k|An End-To-End, Lightweight and Flexible Platform for Game Research|\n|[https://github.com/tensorflow/rust](tensorflow/rust)|1.9k|Rust language bindings for TensorFlow|\n|[https://github.com/awjuliani/DeepRL-Agents](awjuliani/DeepRL-Agents)|1.9k|A set of Deep Reinforcement Learning Agents implemented in Tensorflow.|\n|[https://github.com/lakshayg/tensorflow-build](lakshayg/tensorflow-build)|1.9k|TensorFlow binaries supporting AVX, FMA, SSE|\n|[https://github.com/aleju/papers](aleju/papers)|1.9k|Summaries of machine learning papers|\n|[https://github.com/golbin/TensorFlow-Tutorials](golbin/TensorFlow-Tutorials)|1.9k|텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다|\n|[https://github.com/jolibrain/deepdetect](jolibrain/deepdetect)|1.9k|Deep Learning API and Server in C++11 support for Caffe, Caffe2, TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE|\n|[https://github.com/fo40225/tensorflow-windows-wheel](fo40225/tensorflow-windows-wheel)|1.9k|Tensorflow prebuilt binary for Windows|\n|[https://github.com/robi56/Deep-Learning-for-Recommendation-Systems](robi56/Deep-Learning-for-Recommendation-Systems)|1.9k|This repository contains Deep Learning based articles , paper and repositories for Recommender Systems|\n|[https://github.com/tensorlayer/srgan](tensorlayer/srgan)|1.9k|Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network|\n|[https://github.com/pannous/tensorflow-speech-recognition](pannous/tensorflow-speech-recognition)|1.9k|🎙Speech recognition using the tensorflow deep learning framework, sequence-to-sequence neural networks|\n|[https://github.com/salesforce/decaNLP](salesforce/decaNLP)|1.9k|The Natural Language Decathlon: A Multitask Challenge for NLP|\n|[https://github.com/TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials](TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials)|1.9k|A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding in…|\n|[https://github.com/google/tangent](google/tangent)|1.9k|Source-to-Source Debuggable Derivatives in Pure Python|\n|[https://github.com/shenweichen/DeepCTR](shenweichen/DeepCTR)|1.8k|Easy-to-use,Modular and Extendible package of deep-learning based CTR models.|\n|[https://github.com/tensorflow/docs](tensorflow/docs)|1.8k|TensorFlow documentation|\n|[https://github.com/pytorch/text](pytorch/text)|1.8k|Data loaders and abstractions for text and NLP|\n|[https://github.com/astorfi/TensorFlow-Roadmap](astorfi/TensorFlow-Roadmap)|1.8k|📡 Organized & Useful Resources about Deep Learning with TensorFlow|\n|[https://github.com/avinashpaliwal/Super-SloMo](avinashpaliwal/Super-SloMo)|1.8k|PyTorch implementation of Super SloMo by Jiang et al.|\n|[https://github.com/simoninithomas/Deep_reinforcement_learning_Course](simoninithomas/Deep_reinforcement_learning_Course)|1.8k|Implementations from the free course Deep Reinforcement Learning with Tensorflow|\n|[https://github.com/maciejkula/spotlight](maciejkula/spotlight)|1.8k|Deep recommender models using PyTorch.|\n|[https://github.com/foolwood/SiamMask](foolwood/SiamMask)|1.8k|[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach|\n|[https://github.com/wb14123/seq2seq-couplet](wb14123/seq2seq-couplet)|1.8k|Play couplet with seq2seq model. 用深度学习对对联。|\n|[https://github.com/dmlc/gluon-nlp](dmlc/gluon-nlp)|1.7k|NLP made easy|\n|[https://github.com/philipperemy/keras-attention-mechanism](philipperemy/keras-attention-mechanism)|1.7k|Attention mechanism Implementation for Keras.|\n|[https://github.com/EthicalML/awesome-production-machine-learning](EthicalML/awesome-production-machine-learning)|1.7k|A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning|\n|[https://github.com/wzhe06/Ad-papers](wzhe06/Ad-papers)|1.7k|Papers on Computational Advertising|\n|[https://github.com/szilard/benchm-ml](szilard/benchm-ml)|1.7k|A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Pyt…|\n|[https://github.com/tensorflow/lingvo](tensorflow/lingvo)|1.7k|Lingvo|\n|[https://github.com/google/deepvariant](google/deepvariant)|1.7k|DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA…|\n|[https://github.com/bytedance/byteps](bytedance/byteps)|1.7k|A high performance and general PS framework for distributed training|\n|[https://github.com/tensorflow/hub](tensorflow/hub)|1.7k|A library for transfer learning by reusing parts of TensorFlow models.|\n|[https://github.com/deepchem/deepchem](deepchem/deepchem)|1.7k|Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology|\n|[https://github.com/thu-ml/zhusuan](thu-ml/zhusuan)|1.7k|A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow|\n|[https://github.com/xmartlabs/Bender](xmartlabs/Bender)|1.7k|Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.|\n|[https://github.com/tobegit3hub/tensorflow_template_application](tobegit3hub/tensorflow_template_application)|1.7k|TensorFlow template application for deep learning|\n|[https://github.com/MrNothing/AI-Blocks](MrNothing/AI-Blocks)|1.7k|A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!|\n|[https://github.com/GauravBh1010tt/DeepLearn](GauravBh1010tt/DeepLearn)|1.7k|Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.|\n|[https://github.com/nl8590687/ASRT_SpeechRecognition](nl8590687/ASRT_SpeechRecognition)|1.7k|A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统|\n|[https://github.com/GeorgeSeif/Semantic-Segmentation-Suite](GeorgeSeif/Semantic-Segmentation-Suite)|1.7k|Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!|\n|[https://github.com/abhshkdz/ai-deadlines](abhshkdz/ai-deadlines)|1.7k|⏰ AI conference deadline countdowns|\n|[https://github.com/taolei87/sru](taolei87/sru)|1.7k|Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)|\n|[https://github.com/Picovoice/Porcupine](Picovoice/Porcupine)|1.7k|On-device wake word detection powered by deep learning.|\n|[https://github.com/junxiaosong/AlphaZero_Gomoku](junxiaosong/AlphaZero_Gomoku)|1.7k|An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)|\n|[https://github.com/NVlabs/MUNIT](NVlabs/MUNIT)|1.7k|Multimodal Unsupervised Image-to-Image Translation|\n|[https://github.com/Azure/mmlspark](Azure/mmlspark)|1.6k|Microsoft Machine Learning for Apache Spark|\n|[https://github.com/SummitKwan/transparent_latent_gan](SummitKwan/transparent_latent_gan)|1.6k|Use supervised learning to illuminate the latent space of GAN for controlled generation and edit|\n|[https://github.com/floodsung/Meta-Learning-Papers](floodsung/Meta-Learning-Papers)|1.6k|Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning|\n|[https://github.com/FluxML/Flux.jl](FluxML/Flux.jl)|1.6k|Relax! Flux is the ML library that doesn't make you tensor|\n|[https://github.com/sachinruk/deepschool.io](sachinruk/deepschool.io)|1.6k|Deep Learning tutorials in jupyter notebooks.|\n|[https://github.com/keithito/tacotron](keithito/tacotron)|1.6k|A TensorFlow implementation of Google's Tacotron speech synthesis with pre-trained model (unofficial)|\n|[https://github.com/leoxiaobin/deep-high-resolution-net.pytorch](leoxiaobin/deep-high-resolution-net.pytorch)|1.6k|The project is an official implementation of our CVPR2019 paper \"Deep High-Resolution Representation Learning for Hum…|\n|[https://github.com/microsoft/VoTT](microsoft/VoTT)|1.6k|Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.|\n|[https://github.com/alibaba/euler](alibaba/euler)|1.6k|A distributed graph deep learning framework.|\n|[https://github.com/NVIDIA/DALI](NVIDIA/DALI)|1.6k|A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep le…|\n|[https://github.com/Honlan/DeepInterests](Honlan/DeepInterests)|1.6k|深度有趣|\n|[https://github.com/dmlc/nnvm](dmlc/nnvm)|1.6k|move to https://github.com/dmlc/tvm/|\n|[https://github.com/deepmind/dm_control](deepmind/dm_control)|1.6k|The DM Control Suite and Package is a tool for developing and testing reinforcement learning agents for the MuJoCo ph…|\n|[https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail](ikostrikov/pytorch-a2c-ppo-acktr-gail)|1.5k|PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region met…|\n|[https://github.com/INTERMT/Awesome-PyTorch-Chinese](INTERMT/Awesome-PyTorch-Chinese)|1.5k|【干货】史上最全的PyTorch学习资源汇总|\n|[https://github.com/carpedm20/deep-rl-tensorflow](carpedm20/deep-rl-tensorflow)|1.5k|TensorFlow implementation of Deep Reinforcement Learning papers|\n|[https://github.com/intel/mkl-dnn](intel/mkl-dnn)|1.5k|Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN)|\n|[https://github.com/minimaxir/automl-gs](minimaxir/automl-gs)|1.5k|Provide an input CSV and a target field to predict, generate a model + code to run it.|\n|[https://github.com/sksq96/pytorch-summary](sksq96/pytorch-summary)|1.5k|Model summary in PyTorch similar to `model.summary()` in Keras|\n|[https://github.com/kenshohara/3D-ResNets-PyTorch](kenshohara/3D-ResNets-PyTorch)|1.5k|3D ResNets for Action Recognition (CVPR 2018)|\n|[https://github.com/Zeta36/chess-alpha-zero](Zeta36/chess-alpha-zero)|1.5k|Chess reinforcement learning by AlphaGo Zero methods.|\n|[https://github.com/experiencor/keras-yolo2](experiencor/keras-yolo2)|1.5k|Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon…|\n|[https://github.com/asyml/texar](asyml/texar)|1.5k|Toolkit for Machine Learning and Text Generation, in TensorFlow|\n|[https://github.com/Qihoo360/XLearning](Qihoo360/XLearning)|1.5k|AI on Hadoop|\n|[https://github.com/rguthrie3/DeepLearningForNLPInPytorch](rguthrie3/DeepLearningForNLPInPytorch)|1.5k|An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.|\n|[https://github.com/Kyubyong/tacotron](Kyubyong/tacotron)|1.5k|A TensorFlow Implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model|\n|[https://github.com/tomlepaine/fast-wavenet](tomlepaine/fast-wavenet)|1.5k|Speedy Wavenet generation using dynamic programming ⚡️|\n|[https://github.com/erhwenkuo/deep-learning-with-keras-notebooks](erhwenkuo/deep-learning-with-keras-notebooks)|1.5k|Jupyter notebooks for using & learning Keras|\n|[https://github.com/guillaumegenthial/sequence_tagging](guillaumegenthial/sequence_tagging)|1.5k|Named Entity Recognition (LSTM + CRF) - Tensorflow|\n|[https://github.com/williamFalcon/pytorch-lightning](williamFalcon/pytorch-lightning)|1.5k|Rapid research framework for PyTorch. The researcher's version of Keras|\n|[https://github.com/ajbrock/BigGAN-PyTorch](ajbrock/BigGAN-PyTorch)|1.5k|The author's officially unofficial PyTorch BigGAN implementation.|\n|[https://github.com/autorope/donkeycar](autorope/donkeycar)|1.5k|Open source hardware and software platform to build a small scale self driving car.|\n|[https://github.com/keplr-io/quiver](keplr-io/quiver)|1.5k|Interactive convnet features visualization for Keras|\n|[https://github.com/tensorflow/datasets](tensorflow/datasets)|1.5k|A collection of datasets ready to use with TensorFlow|\n|[https://github.com/knazeri/edge-connect](knazeri/edge-connect)|1.4k|EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. https://arxiv.org/abs/1901.00212|\n|[https://github.com/suragnair/alpha-zero-general](suragnair/alpha-zero-general)|1.4k|A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4|\n|[https://github.com/NervanaSystems/coach](NervanaSystems/coach)|1.4k|Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learnin…|\n|[https://github.com/microsoft/AutonomousDrivingCookbook](microsoft/AutonomousDrivingCookbook)|1.4k|Scenarios, tutorials and demos for Autonomous Driving|\n|[https://github.com/microsoft/human-pose-estimation.pytorch](microsoft/human-pose-estimation.pytorch)|1.4k|The project is an official implement of our ECCV2018 paper \"Simple Baselines for Human Pose Estimation and Tracking(h…|\n|[https://github.com/alexsosn/iOS_ML](alexsosn/iOS_ML)|1.4k|List of Machine Learning, AI, NLP solutions for iOS. The most recent version of this article can be found on my blog.|\n|[https://github.com/ahangchen/GDLnotes](ahangchen/GDLnotes)|1.4k|Google Deep Learning Notes（TensorFlow教程）|\n|[https://github.com/Roujack/mathAI](Roujack/mathAI)|1.4k|一个拍照做题程序。输入一张包含数学计算题的图片，输出识别出的数学计算式以及计算结果。This is a mathematic expression recognition project.|\n|[https://github.com/bfortuner/ml-cheatsheet](bfortuner/ml-cheatsheet)|1.4k|Machine learning cheatsheet|\n|[https://github.com/kaonashi-tyc/zi2zi](kaonashi-tyc/zi2zi)|1.4k|Learning Chinese Character style with conditional GAN|\n|[https://github.com/amusi/AI-Job-Notes](amusi/AI-Job-Notes)|1.4k|AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）|\n|[https://github.com/kevinhughes27/TensorKart](kevinhughes27/TensorKart)|1.4k|self-driving MarioKart with TensorFlow|\n|[https://github.com/dragen1860/TensorFlow-2.x-Tutorials](dragen1860/TensorFlow-2.x-Tutorials)|1.4k|TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT exampl…|\n|[https://github.com/SeldonIO/seldon-server](SeldonIO/seldon-server)|1.4k|Machine Learning Platform and Recommendation Engine built on Kubernetes|\n|[https://github.com/deeplearningturkiye/turkce-yapay-zeka-kaynaklari](deeplearningturkiye/turkce-yapay-zeka-kaynaklari)|1.4k|Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.|\n|[https://github.com/CSAILVision/gandissect](CSAILVision/gandissect)|1.4k|Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/|\n|[https://github.com/ybayle/awesome-deep-learning-music](ybayle/awesome-deep-learning-music)|1.4k|List of articles related to deep learning applied to music|\n|[https://github.com/tqchen/tinyflow](tqchen/tinyflow)|1.4k|Tutorial code on how to build your own Deep Learning System in 2k Lines|\n|[https://github.com/Determined22/zh-NER-TF](Determined22/zh-NER-TF)|1.4k|A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)|\n|[https://github.com/mingyuliutw/UNIT](mingyuliutw/UNIT)|1.4k|Unsupervised Image-to-Image Translation|\n|[https://github.com/PetrochukM/PyTorch-NLP](PetrochukM/PyTorch-NLP)|1.4k|Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers)|\n|[https://github.com/KupynOrest/DeblurGAN](KupynOrest/DeblurGAN)|1.4k|Image Deblurring using Generative Adversarial Networks|\n|[https://github.com/Franck-Dernoncourt/NeuroNER](Franck-Dernoncourt/NeuroNER)|1.3k|Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.|\n|[https://github.com/ncullen93/torchsample](ncullen93/torchsample)|1.3k|High-Level Training, Data Augmentation, and Utilities for Pytorch|\n|[https://github.com/onnx/models](onnx/models)|1.3k|A collection of pre-trained, state-of-the-art models in the ONNX format|\n|[https://github.com/pkmital/CADL](pkmital/CADL)|1.3k|Course materials/Homework materials for the FREE MOOC course on \"Creative Applications of Deep Learning w/ Tensorflow…|\n|[https://github.com/philipperemy/tensorflow-1.4-billion-password-analysis](philipperemy/tensorflow-1.4-billion-password-analysis)|1.3k|Deep Learning model to analyze a large corpus of clear text passwords.|\n|[https://github.com/YunYang1994/tensorflow-yolov3](YunYang1994/tensorflow-yolov3)|1.3k|🔥 pure tensorflow Implement of YOLOv3 with support to train your own dataset|\n|[https://github.com/hanleyweng/CoreML-in-ARKit](hanleyweng/CoreML-in-ARKit)|1.3k|Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit…|\n|[https://github.com/NVIDIA/DeepRecommender](NVIDIA/DeepRecommender)|1.3k|Deep learning for recommender systems|\n|[https://github.com/RiweiChen/DeepFace](RiweiChen/DeepFace)|1.3k|Face analysis mainly based on Caffe. At this time, face analysis tasks like detection, alignment and recognition have…|\n|[https://github.com/DT42/BerryNet](DT42/BerryNet)|1.3k|Deep learning gateway on Raspberry Pi and other edge devices|\n|[https://github.com/microsoft/pai](microsoft/pai)|1.2k|Resource scheduling and cluster management for AI|\n"}, "235cef40a3099db2ab86dfef6e1ca272ea5e20d0": {"t": 1785772727.3946047, "n": 8301, "h": "9142a8dfe1b0aacd", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [dl-setup](https://github.com/saiprashanths/dl-setup) | 1607 | Instructions for setting up the software on your deep learning machine.\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Tiny DNN](https://github.com/tiny-dnn/tiny-dnn) | 1183 | header only, dependency-free deep learning framework in C++11\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [dl-docker](https://github.com/saiprashanths/dl-docker) | 1044 | An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.).\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [MatConvNet](https://github.com/vlfeat/matconvnet)| 479 | MATLAB CNN toolbox for computer vision applications.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n| [Visual Search Server](https://github.com/AKSHAYUBHAT/VisualSearchServer)| 304 | Visual Search using Tensorflow inception model & Approximate Nearest Neighbors.\n"}, "0d2a771f20915446a637ba5b1c8eef42385a9f41": {"t": 1785772728.96736, "n": 8179, "h": "47ca2a927a3583dd", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [dl-setup](https://github.com/saiprashanths/dl-setup) | 1607 | Instructions for setting up the software on your deep learning machine.\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [dl-docker](https://github.com/saiprashanths/dl-docker) | 1044 | An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.).\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [MatConvNet](https://github.com/vlfeat/matconvnet)| 479 | MATLAB CNN toolbox for computer vision applications.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n| [Visual Search Server](https://github.com/AKSHAYUBHAT/VisualSearchServer)| 304 | Visual Search using Tensorflow inception model & Approximate Nearest Neighbors.\n"}, "3e1ca5f681091a0c6bfa53ec44709d9476e93783": {"t": 1785772730.178525, "n": 7848, "h": "8916759c582d082e", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [MatConvNet](https://github.com/vlfeat/matconvnet)| 479 | MATLAB CNN toolbox for computer vision applications.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n| [Visual Search Server](https://github.com/AKSHAYUBHAT/VisualSearchServer)| 304 | Visual Search using Tensorflow inception model & Approximate Nearest Neighbors.\n"}, "ddf8fbee8ddf0ba1fa4c686e4b95c685f101728f": {"t": 1785772731.3843467, "n": 8073, "h": "5b0a9168a3000b9a", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Nupic](https://github.com/numenta/nupic) | 4364 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [MatConvNet](https://github.com/vlfeat/matconvnet)| 479 | MATLAB CNN toolbox for computer vision applications.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n| [Visual Search Server](https://github.com/AKSHAYUBHAT/VisualSearchServer)| 304 | Visual Search using Tensorflow inception model & Approximate Nearest Neighbors.\n"}, "4a46dedb47dc91efbae1cfab4583ef8542aaf8e8": {"t": 1785772734.336027, "n": 7910, "h": "9d2fdacff75524bb", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Nupic](https://github.com/numenta/nupic) | 4364 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [MatConvNet](https://github.com/vlfeat/matconvnet)| 479 | MATLAB CNN toolbox for computer vision applications.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n"}, "01a309d7dc5f09a3732ce418bea89e7187013b16": {"t": 1785772735.4998667, "n": 7797, "h": "94d9610f0011e7f5", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Nupic](https://github.com/numenta/nupic) | 4364 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Darknet](https://github.com/pjreddie/darknet) | 937 | Open Source Neural Networks in C\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n"}, "8ca5a018fa40ec1ccadaf66ac21616bfca47f4af": {"t": 1785772736.9248443, "n": 7707, "h": "495e5fd6f375f47a", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Nupic](https://github.com/numenta/nupic) | 4364 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n"}, "9430d9e6c7aa7604e8383feb392ac047f07e5e3f": {"t": 1785772738.2496176, "n": 7707, "h": "3983c8363f4b6dd3", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.08.09\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 29622 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 11799 | Caffe: a fast open framework for deep learning.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 10148 | Torch implementation of neural style algorithm.\n| [Deep Dream](https://github.com/google/deepdream) | 9042 | Deep Dream.\n| [Keras](https://github.com/fchollet/keras) | 7502 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 7170 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [TensorFlow Models](https://github.com/tensorflow/models) | 6671 | Models built with TensorFlow\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 6275 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5957 | Computational Network Toolkit (CNTK).\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 5872 | TensorFlow tutorials and code examples for beginners.\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 5231 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 5133 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4855 | Face recognition with deep neural networks.\n| [MXNet](https://github.com/dmlc/mxnet) | 4685 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Nupic](https://github.com/numenta/nupic) | 4364 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Theano](https://github.com/Theano/Theano) | 4286 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Leaf](https://github.com/autumnai/leaf) | 4281 | Open Machine Intelligence Framework for Hackers.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3820 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3694 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 3673 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TFLearn](https://github.com/tflearn/tflearn) | 3368 | Deep learning library featuring a higher-level API for TensorFlow.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 3352 | Play with neural networks!\n| [OpenAI Gym](https://github.com/openai/gym) | 3020 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Magenta](https://github.com/tensorflow/magenta) | 2914 | Magenta: Music and Art Generation with Machine Intelligence\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2798 | Neural Network to colorize grayscale images.\n| [Synaptic](https://github.com/cazala/synaptic) | 2666 | architecture-free neural network library for node.js and the browser\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2540 | Generate image analogies using neural matching and blending.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2550 | Efficient Image Captioning code in Torch, runs on GPU.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2413 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2355 | Lightweight library to build and train neural networks in Theano.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2153 | A Machine Learning library based on Theano.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 2134 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Neon](https://github.com/NervanaSystems/neon) | 2121 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 2032 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1721 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Chainer](https://github.com/pfnet/chainer) | 1573 | A flexible framework of neural networks for deep learning.\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1514 | A recurrent neural network for generating little stories about images.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1353 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1229 | Deep learning driven jazz generation using Keras & Theano!\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1143 | Fast, flexible and fun neural networks.\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 904 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 904 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 866 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 860 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 849 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [Veles](https://github.com/samsung/veles) | 760 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Deep Detect](https://github.com/beniz/deepdetect) | 759 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 759 | A deep Q learning demonstration using Google Tensorflow.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 724 | Caffe On Spark.\n| [Nolearn](https://github.com/dnouri/nolearn) | 702 | Abstractions around neural net libraries, most notably Lasagne.\n| [DCGAN TensorFlow](https://github.com/carpedm20/DCGAN-tensorflow) | 568 | A tensorflow implementation of Deep Convolutional Generative Adversarial Networks\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 413 | OpenCL library to train deep convolutional neural networks.\n"}, "dcdd1811da4366b275765f77a2a287b7cfd4b2b0": {"t": 1785772739.7810764, "n": 7339, "h": "a98a8bcbb4bc1c9f", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.05.02\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [OpenAI Gym](https://github.com/openai/gym) | 1490 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Veles](https://github.com/samsung/veles) | 733 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | Caffe On Spark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n| [DeepCL](https://github.com/hughperkins/DeepCL)| 370 | OpenCL library to train deep convolutional neural networks.\n"}, "210f337caea3d6f0c47335a6af1abc8846f89be6": {"t": 1785772741.1164384, "n": 7223, "h": "8751c419e4521e1d", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.05.02\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [OpenAI Gym](https://github.com/openai/gym) | 1490 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Veles](https://github.com/samsung/veles) | 733 | Distributed machine learning platform (Python, CUDA, OpenCL)\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | Caffe On Spark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n\n"}, "5a5158292268c26fd778f3de99924ba197436eaa": {"t": 1785772742.5492897, "n": 7110, "h": "50adc2d0844917dd", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.05.02\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [OpenAI Gym](https://github.com/openai/gym) | 1490 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | Caffe On Spark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n\n"}, "a708611655a09d1799f25f4a7bc2cf6a6b7be899": {"t": 1785772743.724706, "n": 7091, "h": "08c17d171aeeacdf", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.05.02\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [OpenAI Gym](https://github.com/openai/gym) | 1490 | A toolkit for developing and comparing reinforcement learning algorithms.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | Caffe On Spark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n\n"}, "88cba910254154ceb0a52b9e635375568ead9b26": {"t": 1785772746.1385047, "n": 7089, "h": "6da93c43a5d3f8ae", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.04.28\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | Caffe On Spark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n| [OpenAI Gym](https://github.com/openai/gym) | 406 | A toolkit for developing and comparing reinforcement learning algorithms.\n"}, "ede10256a8de70fbf1e611cc2aa6307bb3d65fbd": {"t": 1785772749.3433604, "n": 7112, "h": "ff0a4fb9a6bcc925", "c": "# Top Deep Learning Projects\nA list of popular github projects related to deep learning (ranked by stars).\n\nLast Update: 2016.04.28\n\n| Project Name| Stars | Description |\n| ------- | ------ | ------ |\n| [TensorFlow](https://github.com/tensorflow/tensorflow) | 22406 | Computation using data flow graphs for scalable machine learning.\n| [Caffe](https://github.com/BVLC/caffe) | 9889 | Caffe: a fast open framework for deep learning.\n| [Deep Dream](https://github.com/google/deepdream) | 8656 | Deep Dream.\n| [Neural Style](https://github.com/jcjohnson/neural-style) | 7569 | Torch implementation of neural style algorithm.\n| [Roc AlphaGo](https://github.com/Rochester-NRT/RocAlphaGo) | 6876 | An independent, student-led replication of DeepMind's 2016 Nature publication, \"Mastering the game of Go with deep neural networks and tree search\" (Nature 529, 484-489, 28 Jan 2016).\n| [Keras](https://github.com/fchollet/keras) | 5765 | Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.\n| [Neural Doodle](https://github.com/alexjc/neural-doodle) | 5499 | Turn your two-bit doodles into fine artworks with deep neural networks, generate seamless textures from photos, transfer style from one image to another, perform example-based upscaling, but wait... there's more! (An implementation of Semantic Style Transfer.)\n| [CNTK](https://github.com/Microsoft/CNTK) | 5286 | Computational Network Toolkit (CNTK).\n| [ConvNet JS](https://github.com/karpathy/convnetjs) | 4640 | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser.\n| [Torch](https://github.com/torch/torch7) | 4437 | Torch7, Deep Learning Library.\n| [OpenFace](https://github.com/cmusatyalab/openface) | 4334 | Face recognition with deep neural networks.\n| [Nupic](https://github.com/numenta/nupic) | 4067 | Numenta Platform for Intelligent Computing: a brain-inspired machine intelligence platform, and biologically accurate neural network based on cortical learning algorithms.\n| [Leaf](https://github.com/autumnai/leaf) | 3940 | Open Machine Intelligence Framework for Hackers.\n| [Theano](https://github.com/Theano/Theano) | 3600 | Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It can use GPUs and perform efficient symbolic differentiation.\n| [Neural Talk](https://github.com/karpathy/neuraltalk) | 3521 | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.\n| [MXNet](https://github.com/dmlc/mxnet) | 3513 | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more.\n| [Char RNN](https://github.com/karpathy/char-rnn) | 3077 | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch.\n| [deeplearning4j](deeplearning4j/deeplearning4j) | 2570 | Deep Learning for Java, Scala & Clojure on Hadoop, Spark.\n| [TensorFlow Playground](https://github.com/tensorflow/playground) | 2518 | Play with neural networks!\n| [TFLearn](https://github.com/tflearn/tflearn) | 2502 | Deep learning library featuring a higher-level API for TensorFlow.\n| [Image Analogies](https://github.com/awentzonline/image-analogies) | 2412 | Generate image analogies using neural matching and blending.\n| [Colornet](https://github.com/pavelgonchar/colornet) | 2385 | Neural Network to colorize grayscale images.\n| [SKFlow](https://github.com/tensorflow/skflow) | 2293 | Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning.\n| [Neural Talk 2](https://github.com/karpathy/neuraltalk2) | 2223 | Efficient Image Captioning code in Torch, runs on GPU.\n| [PyLearn2](https://github.com/lisa-lab/pylearn2) | 2060 | A Machine Learning library based on Theano.\n| [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) | 2027 | From the basics to slightly more interesting applications of Tensorflow.\n| [Lasagne](https://github.com/Lasagne/Lasagne) | 2013 | Lightweight library to build and train neural networks in Theano.\n| [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) | 1961 | TensorFlow tutorials and code examples for beginners.\n| [LISA-lab Deep Learning Tutorials](https://github.com/lisa-lab/DeepLearningTutorials) | 1882 | Deep Learning Tutorial notes and code. See the wiki for more info.\n| [Matlab Deep Learning Toolbox](https://github.com/rasmusbergpalm/DeepLearnToolbox) | 1869 | Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.\n| [Neon](https://github.com/NervanaSystems/neon) | 1790 | Fast, scalable, easy-to-use Python based Deep Learning Framework by Nervana™.\n| [Deep Learning Flappy Bird](https://github.com/yenchenlin1994/DeepLearningFlappyBird) | 1473 | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning).\n| [Neural Story Teller](https://github.com/ryankiros/neural-storyteller) | 1373 | A recurrent neural network for generating little stories about images.\n| [Chainer](https://github.com/pfnet/chainer) | 1339 | A flexible framework of neural networks for deep learning.\n| [Brainstorm](https://github.com/IDSIA/brainstorm) | 1089 | Fast, flexible and fun neural networks.\n| [DIGITS](https://github.com/NVIDIA/DIGITS) | 1075 | Deep Learning GPU Training System.\n| [Deep Jazz](https://github.com/jisungk/deepjazz) | 1002 | Deep learning driven jazz generation using Keras & Theano!\n| [Theano Tutorials](https://github.com/Newmu/Theano-Tutorials) | 811 | Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano.\n| [Scikit Neural Net](https://github.com/aigamedev/scikit-neuralnetwork) | 800 | Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.\n| [RNN Music Composition](https://github.com/hexahedria/biaxial-rnn-music-composition) | 797 | A recurrent neural network designed to generate classical music.\n| [Blocks](https://github.com/mila-udem/blocks) | 773 | A Theano framework for building and training neural networks.\n| [TDB](https://github.com/ericjang/tdb) | 765 | Interactive, node-by-node debugging and visualization for TensorFlow.\n| [Nolearn](https://github.com/dnouri/nolearn) | 640 | Abstractions around neural net libraries, most notably Lasagne.\n| [Caffe on Spark](https://github.com/yahoo/CaffeOnSpark) | 599 | https://github.com/yahoo/CaffeOnSpark.\n| [Deep Detect](https://github.com/beniz/deepdetect) | 543 | Deep Learning API and Server in C++11 with Python bindings and support for Caffe.\n| [TensorFlow DeepQ](https://github.com/nivwusquorum/tensorflow-deepq) | 583 | A deep Q learning demonstration using Google Tensorflow.\n| [OpenAI Gym](https://github.com/openai/gym) | 406 | A toolkit for developing and comparing reinforcement learning algorithms.\n"}, "5c651cc694db669b8ea54fc14bd970a3dfc89f95": {"t": 1785772750.6824102, "n": 77, "h": "d145da4d6338b15b", "c": "# TopDeepLearning\nA list of popular github projects related to deep learning\n"}}}}
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