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https://github.com/mbadry1/top-deep-learning
Top 200 deep learning Github repositories sorted by the number of stars.
https://github.com/mbadry1/top-deep-learning
artificial-intelligence artificial-neural-networks convolutional-neural-networks deep-learning deep-neural-networks deep-reinforcement-learning machine-learning recurrent-neural-networks stargazers-count top-repositories
Last synced: 4 days ago
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Top 200 deep learning Github repositories sorted by the number of stars.
- Host: GitHub
- URL: https://github.com/mbadry1/top-deep-learning
- Owner: mbadry1
- License: mit
- Created: 2018-03-16T00:57:51.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2024-02-17T05:33:18.000Z (11 months ago)
- Last Synced: 2024-10-29T17:52:58.883Z (3 months ago)
- Topics: artificial-intelligence, artificial-neural-networks, convolutional-neural-networks, deep-learning, deep-neural-networks, deep-reinforcement-learning, machine-learning, recurrent-neural-networks, stargazers-count, top-repositories
- Language: Python
- Homepage:
- Size: 135 KB
- Stars: 1,675
- Watchers: 127
- Forks: 429
- Open Issues: 3
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
# Top deep learning Github repositories
Here's a list of top 200 deep learning Github repositories sorted by the number of stars. The query that has been used with Github search API is:
- `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"`
Trending deep learning Github repositories can be found [here](https://github.com/mbadry1/Trending-Deep-Learning).
Date: 02-02-2020 compared to 09-01-2019
Note: This will be updated regularly.
| | Pos | Name | Description | Language | Stars | Forks |
|--------------------|-----|---------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|--------|-------|
| :heavy_minus_sign: | 1 | [tensorflow](https://github.com/tensorflow/tensorflow) | An Open Source Machine Learning Framework for Everyone | C++ | 140574 | 79704 |
| :heavy_minus_sign: | 2 | [keras](https://github.com/keras-team/keras) | Deep Learning for humans | Python | 46627 | 17671 |
| :heavy_minus_sign: | 3 | [opencv](https://github.com/opencv/opencv) | Open Source Computer Vision Library | C++ | 41817 | 32255 |
| :arrow_up:1 | 4 | [DeepLearning-500-questions](https://github.com/scutan90/DeepLearning-500-questions) | 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............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06 | None | 36349 | 11201 |
| :arrow_down:1 | 5 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) | Jupyter Notebook | 36173 | 13657 |
| :heavy_minus_sign: | 6 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 35719 | 8990 |
| :heavy_minus_sign: | 7 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 29775 | 18028 |
| :arrow_up:4 | 8 | [faceswap](https://github.com/deepfakes/faceswap) | Deepfakes Software For All | Python | 28863 | 9258 |
| :new: | 9 | [100-Days-Of-ML-Code](https://github.com/Avik-Jain/100-Days-Of-ML-Code) | 100 Days of ML Coding | Python | 27766 | 6943 |
| :arrow_down:1 | 10 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 27753 | 8098 |
| :arrow_down:1 | 11 | [Deep-Learning-Papers-Reading-Roadmap](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap) | Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! | Python | 25457 | 5818 |
| :new: | 12 | [practicalAI](https://github.com/practicalAI/practicalAI) | 📚 A practical approach to machine learning. | Jupyter Notebook | 23437 | 4171 |
| :arrow_down:2 | 13 | [machine-learning-for-software-engineers](https://github.com/ZuzooVn/machine-learning-for-software-engineers) | A complete daily plan for studying to become a machine learning engineer. | None | 23326 | 5466 |
| :arrow_up:2 | 14 | [AiLearning](https://github.com/apachecn/AiLearning) | AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP | Python | 22923 | 7996 |
| :arrow_down:2 | 15 | [Detectron](https://github.com/facebookresearch/Detectron) | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | Python | 22754 | 5016 |
| :arrow_down:1 | 16 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) | The most cited deep learning papers | TeX | 20574 | 3987 |
| :arrow_up:1 | 17 | [handson-ml](https://github.com/ageron/handson-ml) | A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow. | Jupyter Notebook | 18622 | 10022 |
| :arrow_down:1 | 18 | [incubator-mxnet](https://github.com/apache/incubator-mxnet) | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more | Python | 18344 | 6528 |
| :arrow_up:1 | 19 | [data-science-ipython-notebooks](https://github.com/donnemartin/data-science-ipython-notebooks) | 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. | Python | 17947 | 5528 |
| :arrow_up:1 | 20 | [fastai](https://github.com/fastai/fastai) | The fastai deep learning library, plus lessons and tutorials | Jupyter Notebook | 17001 | 6029 |
| :arrow_down:2 | 21 | [CNTK](https://github.com/microsoft/CNTK) | Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit | C++ | 16658 | 4420 |
| :heavy_minus_sign: | 22 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 16203 | 10402 |
| :arrow_up:15 | 23 | [d2l-zh](https://github.com/d2l-ai/d2l-zh) | 《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。 | Python | 15910 | 4061 |
| :arrow_up:1 | 24 | [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) | OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation | C++ | 15825 | 4682 |
| :arrow_down:2 | 25 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 15643 | 2755 |
| :heavy_minus_sign: | 26 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Python | 15583 | 7251 |
| :arrow_up:4 | 27 | [ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch) | Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning. | Python | 15327 | 2935 |
| :arrow_up:2 | 28 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 15314 | 4813 |
| :arrow_up:62 | 29 | [Real-Time-Voice-Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning) | Clone a voice in 5 seconds to generate arbitrary speech in real-time | Python | 15014 | 2651 |
| :arrow_down:2 | 30 | [100-Days-Of-ML-Code](https://github.com/MLEveryday/100-Days-Of-ML-Code) | 100-Days-Of-ML-Code中文版 | Jupyter Notebook | 14977 | 4170 |
| :arrow_down:4 | 31 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 14565 | 4592 |
| :arrow_down:8 | 32 | [lectures](https://github.com/oxford-cs-deepnlp-2017/lectures) | Oxford Deep NLP 2017 course | None | 14411 | 3477 |
| :arrow_down:4 | 33 | [TensorFlow-Course](https://github.com/machinelearningmindset/TensorFlow-Course) | Simple and ready-to-use tutorials for TensorFlow | Python | 13938 | 2782 |
| :arrow_down:2 | 34 | [Qix](https://github.com/ty4z2008/Qix) | Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang | None | 13091 | 4701 |
| :arrow_down:2 | 35 | [cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai) | Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5 | None | 13068 | 3175 |
| :arrow_down:2 | 36 | [openface](https://github.com/cmusatyalab/openface) | Face recognition with deep neural networks. | Lua | 13043 | 3260 |
| :arrow_up:2 | 37 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 12951 | 2417 |
| :arrow_down:2 | 38 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated JavaScript library for training and deploying ML models. | TypeScript | 12566 | 1040 |
| :arrow_down:4 | 39 | [Screenshot-to-code](https://github.com/emilwallner/Screenshot-to-code) | A neural network that transforms a design mock-up into a static website. | HTML | 12397 | 1226 |
| :arrow_up:49 | 40 | [DeepFaceLab](https://github.com/iperov/DeepFaceLab) | DeepFaceLab is the leading software for creating deep fakes. | Python | 12237 | 2802 |
| :arrow_up:13 | 41 | [deeplearning-models](https://github.com/rasbt/deeplearning-models) | A collection of various deep learning architectures, models, and tips | Jupyter Notebook | 11483 | 2678 |
| :arrow_down:5 | 42 | [deeplearning4j](https://github.com/eclipse/deeplearning4j) | Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark | Java | 11454 | 4803 |
| :arrow_down:2 | 43 | [awesome-datascience](https://github.com/academic/awesome-datascience) | :memo: An awesome Data Science repository to learn and apply for real world problems. | None | 10992 | 3237 |
| :arrow_up:6 | 44 | [pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) | Image-to-Image Translation in PyTorch | Python | 10911 | 3141 |
| :arrow_down:5 | 45 | [pix2code](https://github.com/tonybeltramelli/pix2code) | pix2code: Generating Code from a Graphical User Interface Screenshot | Python | 10709 | 1160 |
| :arrow_down:4 | 46 | [neural-networks-and-deep-learning](https://github.com/mnielsen/neural-networks-and-deep-learning) | Code samples for my book "Neural Networks and Deep Learning" | Python | 10687 | 5046 |
| :arrow_down:3 | 47 | [Paddle](https://github.com/PaddlePaddle/Paddle) | 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、分布式训练和跨平台部署） | C++ | 10676 | 2823 |
| :arrow_up:4 | 48 | [nndl.github.io](https://github.com/nndl/nndl.github.io) | 《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning | HTML | 10517 | 2356 |
| :arrow_up:14 | 49 | [ray](https://github.com/ray-project/ray) | A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. | Python | 10248 | 1484 |
| :arrow_up:32 | 50 | [pytorch-handbook](https://github.com/zergtant/pytorch-handbook) | 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 | Jupyter Notebook | 10163 | 3056 |
| :arrow_down:8 | 51 | [FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle) | Style transfer, deep learning, feature transform | Python | 10052 | 1041 |
| :arrow_up:3 | 52 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 9965 | 4055 |
| :arrow_down:7 | 53 | [char-rnn](https://github.com/karpathy/char-rnn) | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch | Lua | 9953 | 2370 |
| :arrow_down:5 | 54 | [Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials) | machine learning and deep learning tutorials, articles and other resources | None | 9920 | 3029 |
| :arrow_down:10 | 55 | [convnetjs](https://github.com/karpathy/convnetjs) | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser. | JavaScript | 9888 | 1976 |
| :arrow_down:3 | 56 | [stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning) | VIP cheatsheets for Stanford's CS 229 Machine Learning | None | 9888 | 2402 |
| :arrow_down:9 | 57 | [neural-enhance](https://github.com/alexjc/neural-enhance) | Super Resolution for images using deep learning. | Python | 9868 | 1118 |
| :new: | 58 | [nsfw_data_scraper](https://github.com/alex000kim/nsfw_data_scraper) | Collection of scripts to aggregate image data for the purposes of training an NSFW Image Classifier | Shell | 9853 | 2605 |
| :arrow_down:1 | 59 | [awesome-nlp](https://github.com/keon/awesome-nlp) | :book: A curated list of resources dedicated to Natural Language Processing (NLP) | None | 9846 | 1822 |
| :arrow_down:13 | 60 | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | Dive into Machine Learning with Python Jupyter notebook and scikit-learn! | None | 9786 | 1817 |
| :new: | 61 | [spleeter](https://github.com/deezer/spleeter) | Deezer source separation library including pretrained models. | Python | 9752 | 853 |
| :arrow_up:6 | 62 | [labelImg](https://github.com/tzutalin/labelImg) | 🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 9635 | 3282 |
| :arrow_down:3 | 63 | [tensor2tensor](https://github.com/tensorflow/tensor2tensor) | Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. | Python | 9522 | 2456 |
| :arrow_down:8 | 64 | [CycleGAN](https://github.com/junyanz/CycleGAN) | Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more. | Lua | 9419 | 1575 |
| :arrow_down:6 | 65 | [stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials) | This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research. | Python | 9377 | 4273 |
| :arrow_down:15 | 66 | [tflearn](https://github.com/tflearn/tflearn) | Deep learning library featuring a higher-level API for TensorFlow. | Python | 9363 | 2396 |
| :arrow_up:2 | 67 | [deep-learning-with-python-notebooks](https://github.com/fchollet/deep-learning-with-python-notebooks) | Jupyter notebooks for the code samples of the book "Deep Learning with Python" | Jupyter Notebook | 9349 | 4607 |
| :arrow_down:11 | 68 | [turicreate](https://github.com/apple/turicreate) | Turi Create simplifies the development of custom machine learning models. | C++ | 9331 | 949 |
| :arrow_up:7 | 69 | [learnopencv](https://github.com/spmallick/learnopencv) | Learn OpenCV : C++ and Python Examples | Jupyter Notebook | 9264 | 6080 |
| :arrow_up:1 | 70 | [DeOldify](https://github.com/jantic/DeOldify) | A Deep Learning based project for colorizing and restoring old images (and video!) | Jupyter Notebook | 8949 | 988 |
| :arrow_up:2 | 71 | [Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list) | A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc. | None | 8917 | 1954 |
| :arrow_down:6 | 72 | [DeepCreamPy](https://github.com/deeppomf/DeepCreamPy) | Decensoring Hentai with Deep Neural Networks | Python | 8874 | 961 |
| :arrow_down:11 | 73 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) | A curated list of deep learning resources for computer vision | None | 8842 | 2586 |
| :arrow_down:7 | 74 | [fast-style-transfer](https://github.com/lengstrom/fast-style-transfer) | TensorFlow CNN for fast style transfer ⚡🖥🎨🖼 | Python | 8667 | 2160 |
| :arrow_down:10 | 75 | [EffectiveTensorflow](https://github.com/vahidk/EffectiveTensorflow) | TensorFlow 1.x and 2.x tutorials and best practices. | None | 8566 | 964 |
| :arrow_down:15 | 76 | [tfjs-core](https://github.com/tensorflow/tfjs-core) | WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. | TypeScript | 8561 | 988 |
| :arrow_down:5 | 77 | [dlib](https://github.com/davisking/dlib) | A toolkit for making real world machine learning and data analysis applications in C++ | C++ | 8546 | 2547 |
| :heavy_minus_sign: | 78 | [horovod](https://github.com/horovod/horovod) | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. | Python | 8517 | 1330 |
| :arrow_down:15 | 79 | [caffe2](https://github.com/facebookarchive/caffe2) | Caffe2 is a lightweight, modular, and scalable deep learning framework. | Shell | 8482 | 2096 |
| :arrow_down:1 | 80 | [conv_arithmetic](https://github.com/vdumoulin/conv_arithmetic) | A technical report on convolution arithmetic in the context of deep learning | TeX | 8169 | 1591 |
| :arrow_down:11 | 81 | [sonnet](https://github.com/deepmind/sonnet) | TensorFlow-based neural network library | Python | 8138 | 1182 |
| :arrow_down:2 | 82 | [ncnn](https://github.com/Tencent/ncnn) | ncnn is a high-performance neural network inference framework optimized for the mobile platform | C++ | 8071 | 2128 |
| :arrow_up:1 | 83 | [imgaug](https://github.com/aleju/imgaug) | Image augmentation for machine learning experiments. | Python | 8013 | 1603 |
| :arrow_down:9 | 84 | [TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials) | TensorFlow Tutorials with YouTube Videos | Jupyter Notebook | 8007 | 3922 |
| :arrow_down:8 | 85 | [libfacedetection](https://github.com/ShiqiYu/libfacedetection) | An open source library for face detection in images. The face detection speed can reach 1500FPS. | C++ | 7971 | 2267 |
| :arrow_down:5 | 86 | [allennlp](https://github.com/allenai/allennlp) | An open-source NLP research library, built on PyTorch. | Python | 7949 | 1707 |
| :arrow_down:13 | 87 | [MLAlgorithms](https://github.com/rushter/MLAlgorithms) | Minimal and clean examples of machine learning algorithms implementations | Python | 7907 | 1424 |
| :arrow_up:5 | 88 | [netron](https://github.com/lutzroeder/netron) | Visualizer for neural network, deep learning and machine learning models | JavaScript | 7882 | 959 |
| :arrow_up:1 | 89 | [shap](https://github.com/slundberg/shap) | A game theoretic approach to explain the output of any machine learning model. | Jupyter Notebook | 7792 | 1091 |
| :arrow_down:5 | 90 | [onnx](https://github.com/onnx/onnx) | Open Neural Network Exchange | PureBasic | 7792 | 1281 |
| :arrow_down:4 | 91 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents Toolkit | Python | 7685 | 2052 |
| :arrow_down:6 | 92 | [mit-deep-learning-book-pdf](https://github.com/janishar/mit-deep-learning-book-pdf) | MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville | Java | 7534 | 1845 |
| :arrow_down:10 | 93 | [pix2pix](https://github.com/phillipi/pix2pix) | Image-to-image translation with conditional adversarial nets | Lua | 7423 | 1289 |
| :heavy_minus_sign: | 94 | [deep-learning-drizzle](https://github.com/kmario23/deep-learning-drizzle) | Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!! | None | 7284 | 1694 |
| :arrow_down:7 | 95 | [fashion-mnist](https://github.com/zalandoresearch/fashion-mnist) | A MNIST-like fashion product database. Benchmark :point_right: | Python | 7160 | 1564 |
| :arrow_up:1 | 96 | [deep_learning_object_detection](https://github.com/hoya012/deep_learning_object_detection) | A paper list of object detection using deep learning. | None | 7139 | 2009 |
| :new: | 97 | [Dive-into-DL-PyTorch](https://github.com/ShusenTang/Dive-into-DL-PyTorch) | 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。 | Jupyter Notebook | 7092 | 2054 |
| :arrow_up:2 | 98 | [mit-deep-learning](https://github.com/lexfridman/mit-deep-learning) | Tutorials, assignments, and competitions for MIT Deep Learning related courses. | Jupyter Notebook | 6899 | 1543 |
| :arrow_up:25 | 99 | [recommenders](https://github.com/microsoft/recommenders) | Best Practices on Recommendation Systems | Jupyter Notebook | 6899 | 977 |
| :new: | 100 | [Deep-Learning-with-TensorFlow-book](https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book) | 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. | Python | 6771 | 1848 |
| :arrow_up:1 | 101 | [pytorch-book](https://github.com/chenyuntc/pytorch-book) | 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》) | Jupyter Notebook | 6685 | 2453 |
| :arrow_up:7 | 102 | [bert-as-service](https://github.com/hanxiao/bert-as-service) | Mapping a variable-length sentence to a fixed-length vector using BERT model | Python | 6681 | 1357 |
| :new: | 103 | [streamlit](https://github.com/streamlit/streamlit) | Streamlit — The fastest way to build custom ML tools | Python | 6650 | 575 |
| :arrow_down:9 | 104 | [autokeras](https://github.com/keras-team/autokeras) | An AutoML system based on Keras | Python | 6561 | 1058 |
| :arrow_down:13 | 105 | [py-faster-rcnn](https://github.com/rbgirshick/py-faster-rcnn) | Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version | Python | 6551 | 3875 |
| :arrow_up:13 | 106 | [pytorch_geometric](https://github.com/rusty1s/pytorch_geometric) | Geometric Deep Learning Extension Library for PyTorch | Python | 6473 | 1036 |
| :arrow_down:3 | 107 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 6450 | 2323 |
| :arrow_down:9 | 108 | [ludwig](https://github.com/uber/ludwig) | Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. | Python | 6350 | 724 |
| :arrow_down:13 | 109 | [lab](https://github.com/deepmind/lab) | A customisable 3D platform for agent-based AI research | C | 6052 | 1222 |
| :arrow_down:7 | 110 | [deep-learning-models](https://github.com/fchollet/deep-learning-models) | Keras code and weights files for popular deep learning models. | Python | 5959 | 1986 |
| :new: | 111 | [handson-ml2](https://github.com/ageron/handson-ml2) | A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2. | Jupyter Notebook | 5921 | 2144 |
| :arrow_down:6 | 112 | [tensorlayer](https://github.com/tensorlayer/tensorlayer) | Deep Learning and Reinforcement Learning Library for Scientists 🔥 | Python | 5876 | 1344 |
| :arrow_down:15 | 113 | [BossSensor](https://github.com/Hironsan/BossSensor) | Hide screen when boss is approaching. | Python | 5830 | 1091 |
| :arrow_down:4 | 114 | [text_classification](https://github.com/brightmart/text_classification) | all kinds of text classification models and more with deep learning | Python | 5794 | 2200 |
| :new: | 115 | [machine-learning-yearning-cn](https://github.com/deeplearning-ai/machine-learning-yearning-cn) | Machine Learning Yearning 中文版 - 《机器学习训练秘籍》 - Andrew Ng 著 | CSS | 5770 | 1232 |
| :arrow_down:15 | 116 | [Swift-AI](https://github.com/Swift-AI/Swift-AI) | The Swift machine learning library. | Swift | 5666 | 549 |
| :arrow_up:8 | 117 | [python-machine-learning-book-2nd-edition](https://github.com/rasbt/python-machine-learning-book-2nd-edition) | The "Python Machine Learning (2nd edition)" book code repository and info resource | Jupyter Notebook | 5569 | 2288 |
| :arrow_down:13 | 118 | [awesome-rnn](https://github.com/kjw0612/awesome-rnn) | Recurrent Neural Network - A curated list of resources dedicated to RNN | None | 5559 | 1403 |
| :arrow_down:11 | 119 | [DeepLearningFlappyBird](https://github.com/yenchenlin/DeepLearningFlappyBird) | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning). | Python | 5507 | 1808 |
| :arrow_down:13 | 120 | [SerpentAI](https://github.com/SerpentAI/SerpentAI) | Game Agent Framework. Helping you create AIs / Bots to play any game you own! | Jupyter Notebook | 5451 | 607 |
| :arrow_down:10 | 121 | [tensorflow_cookbook](https://github.com/nfmcclure/tensorflow_cookbook) | Code for Tensorflow Machine Learning Cookbook | Jupyter Notebook | 5438 | 2331 |
| :arrow_down:4 | 122 | [AdversarialNetsPapers](https://github.com/zhangqianhui/AdversarialNetsPapers) | The classical paper list with code about generative adversarial nets | None | 5356 | 1824 |
| :arrow_down:8 | 123 | [darkflow](https://github.com/thtrieu/darkflow) | Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices | Python | 5328 | 1909 |
| :arrow_down:12 | 124 | [deepo](https://github.com/ufoym/deepo) | Set up deep learning environment in a single command line. | Python | 5308 | 654 |
| :arrow_up:58 | 125 | [nni](https://github.com/microsoft/nni) | An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning. | Python | 5281 | 676 |
| :arrow_down:10 | 126 | [chainer](https://github.com/chainer/chainer) | A flexible framework of neural networks for deep learning | Python | 5274 | 1369 |
| :arrow_down:6 | 127 | [awesome-artificial-intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) | A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers | None | 5239 | 1117 |
| :arrow_down:5 | 128 | [tensorpack](https://github.com/tensorpack/tensorpack) | A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility | Python | 5213 | 1593 |
| :arrow_down:12 | 129 | [deep-residual-networks](https://github.com/KaimingHe/deep-residual-networks) | Deep Residual Learning for Image Recognition | None | 5193 | 2041 |
| :arrow_up:12 | 130 | [nlp-tutorial](https://github.com/graykode/nlp-tutorial) | Natural Language Processing Tutorial for Deep Learning Researchers | Jupyter Notebook | 5176 | 1387 |
| :arrow_down:11 | 131 | [cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf) | Convolutional Neural Network for Text Classification in Tensorflow | Python | 5107 | 2620 |
| :arrow_down:19 | 132 | [neuraltalk](https://github.com/karpathy/neuraltalk) | NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences. | Python | 5086 | 1333 |
| :arrow_down:19 | 133 | [srez](https://github.com/david-gpu/srez) | Image super-resolution through deep learning | Python | 5079 | 655 |
| :arrow_down:5 | 134 | [xlnet](https://github.com/zihangdai/xlnet) | XLNet: Generalized Autoregressive Pretraining for Language Understanding | Python | 5046 | 976 |
| :arrow_down:13 | 135 | [tiny-dnn](https://github.com/tiny-dnn/tiny-dnn) | header only, dependency-free deep learning framework in C++14 | C++ | 4992 | 1284 |
| :new: | 136 | [incubator-tvm](https://github.com/apache/incubator-tvm) | Open deep learning compiler stack for cpu, gpu and specialized accelerators | Python | 4966 | 1324 |
| :arrow_up:16 | 137 | [awesome-object-detection](https://github.com/amusi/awesome-object-detection) | Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html | None | 4914 | 1474 |
| :arrow_up:16 | 138 | [PySyft](https://github.com/OpenMined/PySyft) | A library for encrypted, privacy preserving machine learning | Python | 4819 | 1073 |
| :arrow_up:11 | 139 | [wav2letter](https://github.com/facebookresearch/wav2letter) | Facebook AI Research's Automatic Speech Recognition Toolkit | C++ | 4806 | 767 |
| :arrow_down:4 | 140 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 4773 | 3710 |
| :arrow_down:14 | 141 | [Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite) | Multi-platform high performance deep learning inference engine (『飞桨』多平台高性能深度学习预测引擎） | C++ | 4770 | 993 |
| :arrow_down:14 | 142 | [TopDeepLearning](https://github.com/aymericdamien/TopDeepLearning) | A list of popular github projects related to deep learning | Python | 4764 | 970 |
| :arrow_up:2 | 143 | [faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch) | A faster pytorch implementation of faster r-cnn | Python | 4764 | 1616 |
| :arrow_down:14 | 144 | [face_classification](https://github.com/oarriaga/face_classification) | Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV. | Python | 4703 | 1388 |
| :arrow_down:19 | 145 | [keras-js](https://github.com/transcranial/keras-js) | Run Keras models in the browser, with GPU support using WebGL | JavaScript | 4685 | 507 |
| :arrow_up:2 | 146 | [photoprism](https://github.com/photoprism/photoprism) | Personal Photo Management powered by Go and Google TensorFlow | Go | 4623 | 258 |
| :arrow_down:13 | 147 | [h2o-3](https://github.com/h2oai/h2o-3) | Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc. | Java | 4580 | 1672 |
| :arrow_down:17 | 148 | [TensorFlow-World](https://github.com/astorfi/TensorFlow-World) | :earth_americas: Simple and ready-to-use tutorials for TensorFlow | Python | 4468 | 426 |
| :heavy_minus_sign: | 149 | [the-incredible-pytorch](https://github.com/ritchieng/the-incredible-pytorch) | The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. | None | 4463 | 883 |
| :new: | 150 | [mediapipe](https://github.com/google/mediapipe) | MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines | C++ | 4458 | 785 |
| :arrow_down:12 | 151 | [keras-rl](https://github.com/keras-rl/keras-rl) | Deep Reinforcement Learning for Keras. | Python | 4445 | 1146 |
| :arrow_down:19 | 152 | [edward](https://github.com/blei-lab/edward) | A probabilistic programming language in TensorFlow. Deep generative models, variational inference. | Jupyter Notebook | 4435 | 780 |
| :arrow_down:7 | 153 | [MMdnn](https://github.com/microsoft/MMdnn) | MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. | Python | 4421 | 839 |
| :arrow_down:22 | 154 | [amazon-dsstne](https://github.com/amzn/amazon-dsstne) | Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models | C++ | 4408 | 762 |
| :new: | 155 | [TensorFlow-2.x-Tutorials](https://github.com/dragen1860/TensorFlow-2.x-Tutorials) | TensorFlow 2.x version's Tutorials and Examples, including CNN, RNN, GAN, Auto-Encoders, FasterRCNN, GPT, BERT examples, etc. TF 2.0版入门实例代码，实战教程。 | Jupyter Notebook | 4348 | 1415 |
| :new: | 156 | [albumentations](https://github.com/albumentations-team/albumentations) | fast image augmentation library and easy to use wrapper around other libraries | Python | 4336 | 576 |
| :arrow_up:9 | 157 | [Grokking-Deep-Learning](https://github.com/iamtrask/Grokking-Deep-Learning) | this repository accompanies the book "Grokking Deep Learning" | Jupyter Notebook | 4313 | 926 |
| :arrow_down:21 | 158 | [machine-learning-mindmap](https://github.com/dformoso/machine-learning-mindmap) | A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning. | None | 4309 | 762 |
| :arrow_down:8 | 159 | [pix2pixHD](https://github.com/NVIDIA/pix2pixHD) | Synthesizing and manipulating 2048x1024 images with conditional GANs | Python | 4299 | 867 |
| :arrow_down:25 | 160 | [neurojs](https://github.com/janhuenermann/neurojs) | A JavaScript deep learning and reinforcement learning library. | JavaScript | 4291 | 365 |
| :arrow_up:34 | 161 | [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling) | Create HTML profiling reports from pandas DataFrame objects | Python | 4290 | 588 |
| :arrow_up:5 | 162 | [PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial) | Build your neural network easy and fast | Jupyter Notebook | 4286 | 1984 |
| :arrow_down:3 | 163 | [machine_learning_examples](https://github.com/lazyprogrammer/machine_learning_examples) | A collection of machine learning examples and tutorials. | Python | 4232 | 4100 |
| :arrow_down:20 | 164 | [Realtime_Multi-Person_Pose_Estimation](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation) | Code repo for realtime multi-person pose estimation in CVPR'17 (Oral) | Jupyter Notebook | 4190 | 1252 |
| :arrow_down:25 | 165 | [deeplearning-papernotes](https://github.com/dennybritz/deeplearning-papernotes) | Summaries and notes on Deep Learning research papers | None | 4162 | 891 |
| :arrow_down:23 | 166 | [sketch-code](https://github.com/ashnkumar/sketch-code) | Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images. | Python | 4148 | 534 |
| :arrow_down:8 | 167 | [serving](https://github.com/tensorflow/serving) | A flexible, high-performance serving system for machine learning models | C++ | 4148 | 1663 |
| :arrow_down:6 | 168 | [graph_nets](https://github.com/deepmind/graph_nets) | Build Graph Nets in Tensorflow | Python | 4127 | 612 |
| :arrow_down:22 | 169 | [tensorspace](https://github.com/tensorspace-team/tensorspace) | Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js | JavaScript | 4093 | 363 |
| :arrow_up:15 | 170 | [book](https://github.com/KeKe-Li/book) | :books: All programming languages books | None | 4071 | 1492 |
| :new: | 171 | [seq2seq-couplet](https://github.com/wb14123/seq2seq-couplet) | Play couplet with seq2seq model. 用深度学习对对联。 | Python | 4060 | 813 |
| :arrow_up:9 | 172 | [spinningup](https://github.com/openai/spinningup) | An educational resource to help anyone learn deep reinforcement learning. | Python | 4030 | 820 |
| :arrow_down:32 | 173 | [DeepLearningProject](https://github.com/Spandan-Madan/DeepLearningProject) | An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch. | HTML | 4028 | 614 |
| :arrow_down:13 | 174 | [stanford-cs-230-deep-learning](https://github.com/afshinea/stanford-cs-230-deep-learning) | VIP cheatsheets for Stanford's CS 230 Deep Learning | None | 4017 | 816 |
| :arrow_up:11 | 175 | [labelme](https://github.com/wkentaro/labelme) | Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation). | Python | 4000 | 1275 |
| :arrow_down:18 | 176 | [vrn](https://github.com/AaronJackson/vrn) | :man: Code for "Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression" | Shell | 3951 | 659 |
| :new: | 177 | [dgl](https://github.com/dmlc/dgl) | Python package built to ease deep learning on graph, on top of existing DL frameworks. | Python | 3944 | 656 |
| :arrow_down:26 | 178 | [learning-to-learn](https://github.com/deepmind/learning-to-learn) | Learning to Learn in TensorFlow | Python | 3934 | 587 |
| :arrow_up:19 | 179 | [MVision](https://github.com/Ewenwan/MVision) | 机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶 | C++ | 3914 | 1699 |
| :arrow_down:6 | 180 | [DeepPavlov](https://github.com/deepmipt/DeepPavlov) | An open source library for deep learning end-to-end dialog systems and chatbots. | Python | 3912 | 720 |
| :new: | 181 | [models](https://github.com/PaddlePaddle/models) | Pre-trained and Reproduced Deep Learning Models （『飞桨』官方模型库，包含多种学术前沿和工业场景验证的深度学习模型） | Python | 3910 | 1839 |
| :arrow_down:25 | 182 | [DIGITS](https://github.com/NVIDIA/DIGITS) | Deep Learning GPU Training System | HTML | 3899 | 1386 |
| :arrow_up:7 | 183 | [carla](https://github.com/carla-simulator/carla) | Open-source simulator for autonomous driving research. | C++ | 3885 | 1058 |
| :arrow_down:29 | 184 | [DeepLearningTutorials](https://github.com/lisa-lab/DeepLearningTutorials) | Deep Learning Tutorial notes and code. See the wiki for more info. | Python | 3882 | 2137 |
| :arrow_down:21 | 185 | [DenseNet](https://github.com/liuzhuang13/DenseNet) | Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). | Lua | 3833 | 923 |
| :arrow_down:30 | 186 | [neon](https://github.com/NervanaSystems/neon) | Intel® Nervana™ reference deep learning framework committed to best performance on all hardware | Python | 3821 | 847 |
| :arrow_down:7 | 187 | [OpenNMT-py](https://github.com/OpenNMT/OpenNMT-py) | Open Source Neural Machine Translation in PyTorch | Python | 3802 | 1453 |
| :arrow_down:25 | 188 | [DeepLearningZeroToAll](https://github.com/hunkim/DeepLearningZeroToAll) | TensorFlow Basic Tutorial Labs | Jupyter Notebook | 3798 | 2394 |
| :new: | 189 | [d2l-en](https://github.com/d2l-ai/d2l-en) | Dive into Deep Learning: an interactive deep learning book with code, math, and discussions, based on the NumPy interface. | Python | 3790 | 976 |
| :arrow_down:17 | 190 | [Augmentor](https://github.com/mdbloice/Augmentor) | Image augmentation library in Python for machine learning. | Jupyter Notebook | 3767 | 714 |
| :arrow_down:21 | 191 | [Deep-Learning-21-Examples](https://github.com/hzy46/Deep-Learning-21-Examples) | 《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码 | Python | 3750 | 1637 |
| :arrow_down:20 | 192 | [mace](https://github.com/XiaoMi/mace) | MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms. | C++ | 3735 | 662 |
| :arrow_down:17 | 193 | [Practical_RL](https://github.com/yandexdataschool/Practical_RL) | A course in reinforcement learning in the wild | Jupyter Notebook | 3716 | 1082 |
| :arrow_down:29 | 194 | [dl-docker](https://github.com/floydhub/dl-docker) | An all-in-one Docker image for deep learning. Contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, etc.) | Python | 3706 | 823 |
| :arrow_down:27 | 195 | [deep-learning-roadmap](https://github.com/machinelearningmindset/deep-learning-roadmap) | :satellite: All You Need to Know About Deep Learning - A kick-starter | Python | 3680 | 565 |
| :arrow_down:21 | 196 | [SSD-Tensorflow](https://github.com/balancap/SSD-Tensorflow) | Single Shot MultiBox Detector in TensorFlow | Jupyter Notebook | 3651 | 1779 |
| :arrow_down:28 | 197 | [MachineLearning](https://github.com/wepe/MachineLearning) | Basic Machine Learning and Deep Learning | Python | 3648 | 2722 |
| :new: | 198 | [machine-learning-notes](https://github.com/roboticcam/machine-learning-notes) | My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (1500+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(1500+页)和视频链接 | Jupyter Notebook | 3612 | 1007 |
| :new: | 199 | [ML-NLP](https://github.com/NLP-LOVE/ML-NLP) | 此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。 | Jupyter Notebook | 3603 | 1073 |
| :arrow_down:9 | 200 | [attention-is-all-you-need-pytorch](https://github.com/jadore801120/attention-is-all-you-need-pytorch) | A PyTorch implementation of the Transformer model in "Attention is All You Need". | Python | 3603 | 953 |