├── .gitattributes ├── LICENSE ├── Old-lists ├── 03-27-2018.md ├── 03-28-2018.md ├── 03-31-2018.md ├── 04-02-2019.md ├── 04-03-2018.md ├── 04-05-2018.md ├── 04-10-2018.md ├── 04-25-2018.md ├── 04-29-2018.md ├── 06-10-2018.md ├── 06-26-2019.md ├── 07-16-2018.md └── 09-01-2019.md ├── main.py └── readme.md /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2018 MBadry 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. -------------------------------------------------------------------------------- /Old-lists/03-28-2018.md: -------------------------------------------------------------------------------- 1 | # Trending deep learning Github repositories 2 | 3 | Here's a list of top 100 deep learning Github trending repositories sorted by the number of stars gained on a specific day. The query that has been used with Github search API is: 4 | 5 | - `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"` 6 | 7 | Repositories with 50000 or more are excluded. 8 | 9 | Top deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning). 10 | 11 | Date: 03-28-2018 compared to 03-27-2018 12 | 13 | Hint: This will be updated regularly. 14 | 15 | 16 | | | Pos1 | Name | Description | Language | Stars Today | Total Stars | 17 | |--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------| 18 | | :arrow_up:1 | 1 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 131 | 6646 | 19 | | :new: | 2 | [tensornets](https://github.com/taehoonlee/tensornets) | High level network definitions with pre-trained weights in TensorFlow | Python | 67 | 382 | 20 | | :arrow_up:4 | 3 | [FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle) | Style transfer, deep learning, feature transform | Python | 60 | 7795 | 21 | | :arrow_up:50 | 4 | [Screenshot-to-code-in-Keras](https://github.com/emilwallner/Screenshot-to-code-in-Keras) | A neural network that transforms a screenshot into a static website | Jupyter Notebook | 55 | 9939 | 22 | | :heavy_minus_sign: | 5 | [keras](https://github.com/keras-team/keras) | Deep Learning for humans | Python | 51 | 27518 | 23 | | :arrow_up:35 | 6 | [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 | 50 | 616 | 24 | | :arrow_down:6 | 7 | [RL-Adventure](https://github.com/higgsfield/RL-Adventure) | Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code. | Jupyter Notebook | 43 | 640 | 25 | | :arrow_up:3 | 8 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 35 | 16730 | 26 | | :arrow_up:7 | 9 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) | Curated list of Machine Learning, NLP, Vision Project Ideas | None | 33 | 465 | 27 | | :arrow_down:1 | 10 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | Python | 32 | 13315 | 28 | | :arrow_up:9 | 11 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners with Latest APIs | Jupyter Notebook | 32 | 21036 | 29 | | :arrow_up:18 | 12 | [fastai](https://github.com/fastai/fastai) | The fast.ai deep learning library, lessons, and tutorials | Jupyter Notebook | 30 | 3813 | 30 | | :arrow_down:3 | 13 | [opencv](https://github.com/opencv/opencv) | Open Source Computer Vision Library | C++ | 27 | 23294 | 31 | | :arrow_down:2 | 14 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Jupyter Notebook | 24 | 4589 | 32 | | :arrow_down:1 | 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 | 23 | 13069 | 33 | | :arrow_up:68 | 16 | [tensorlayer](https://github.com/tensorlayer/tensorlayer) | TensorLayer: A Deep Learning and Reinforcement Learning Library for Researchers and Engineers. | Python | 23 | 3511 | 34 | | :arrow_up:1 | 17 | [deeplearnjs](https://github.com/PAIR-code/deeplearnjs) | Hardware-accelerated deep learning // machine learning // NumPy library for the web. | TypeScript | 21 | 6936 | 35 | | :arrow_down:12 | 18 | [Augmentor](https://github.com/mdbloice/Augmentor) | Image augmentation library in Python for machine learning. | Python | 21 | 784 | 36 | | :arrow_down:2 | 19 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 19 | 23453 | 37 | | :arrow_down:7 | 20 | [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 | 19 | 6561 | 38 | | :arrow_up:19 | 21 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 18 | 8765 | 39 | | :arrow_up:14 | 22 | [awesome-nlp](https://github.com/keon/awesome-nlp) | :book: A curated list of resources dedicated to Natural Language Processing (NLP) | None | 17 | 4502 | 40 | | :arrow_down:8 | 23 | [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) | OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation | C++ | 17 | 6449 | 41 | | :arrow_down:5 | 24 | [Deep-Learning-Papers-Reading-Roadmap](https://github.com/songrotek/Deep-Learning-Papers-Reading-Roadmap) | Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! | Python | 17 | 16517 | 42 | | :arrow_up:23 | 25 | [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 | 17 | 13492 | 43 | | :arrow_down:2 | 26 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 16 | 8308 | 44 | | :arrow_up:19 | 27 | [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 | 15 | 2650 | 45 | | :arrow_down:20 | 28 | [DeepLearningFrameworks](https://github.com/ilkarman/DeepLearningFrameworks) | Demo of running NNs across different frameworks | Jupyter Notebook | 15 | 1010 | 46 | | :arrow_up:26 | 29 | [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 | 14 | 2492 | 47 | | :arrow_up:34 | 30 | [Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials) | machine learning and deep learning tutorials, articles and other resources | None | 14 | 7025 | 48 | | :arrow_down:3 | 31 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 14 | 5041 | 49 | | :arrow_up:40 | 32 | [CycleGAN](https://github.com/junyanz/CycleGAN) | Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more. | Lua | 14 | 6018 | 50 | | :arrow_up:47 | 33 | [pix2code](https://github.com/tonybeltramelli/pix2code) | pix2code: Generating Code from a Graphical User Interface Screenshot | Python | 13 | 8815 | 51 | | :arrow_down:9 | 34 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents | C# | 13 | 2517 | 52 | | :arrow_down:14 | 35 | [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 | 12 | 5632 | 53 | | :arrow_down:14 | 36 | [ray](https://github.com/ray-project/ray) | A high-performance distributed execution engine | Python | 12 | 2837 | 54 | | :arrow_down:6 | 37 | [labelImg](https://github.com/tzutalin/labelImg) | :metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 12 | 2775 | 55 | | :new: | 38 | [pytorch-book](https://github.com/chenyuntc/pytorch-book) | PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation | Jupyter Notebook | 12 | 797 | 56 | | :arrow_up:47 | 39 | [EffectiveTensorflow](https://github.com/vahidk/EffectiveTensorflow) | TensorFlow tutorials and best practices. | None | 11 | 7064 | 57 | | :arrow_up:49 | 40 | [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | Deep Learning for Java, Scala & Clojure on Hadoop & Spark With GPUs - From Skymind | Java | 11 | 8579 | 58 | | :arrow_down:37 | 41 | [Netron](https://github.com/lutzroeder/Netron) | Visualizer for deep learning and machine learning models | JavaScript | 11 | 558 | 59 | | :arrow_up:23 | 42 | [zhihu](https://github.com/NELSONZHAO/zhihu) | 知乎专栏源码 | Jupyter Notebook | 11 | 732 | 60 | | :new: | 43 | [conv_arithmetic](https://github.com/vdumoulin/conv_arithmetic) | A technical report on convolution arithmetic in the context of deep learning | TeX | 11 | 3356 | 61 | | :arrow_up:7 | 44 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) | The most cited deep learning papers | TeX | 11 | 14186 | 62 | | :arrow_up:13 | 45 | [caffe2](https://github.com/caffe2/caffe2) | Caffe2 is a lightweight, modular, and scalable deep learning framework. | C++ | 11 | 7685 | 63 | | :arrow_up:13 | 46 | [ncnn](https://github.com/Tencent/ncnn) | ncnn is a high-performance neural network inference framework optimized for the mobile platform | C++ | 11 | 3538 | 64 | | :new: | 47 | [faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch) | A faster pytorch implementation of faster r-cnn | Python | 11 | 970 | 65 | | :new: | 48 | [DeblurGAN](https://github.com/KupynOrest/DeblurGAN) | Image Deblurring using Generative Adversarial Networks | Python | 11 | 721 | 66 | | :arrow_up:4 | 49 | [TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials) | TensorFlow Tutorials with YouTube Videos | Jupyter Notebook | 10 | 3708 | 67 | | :arrow_down:15 | 50 | [CNTK](https://github.com/Microsoft/CNTK) | Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit | C++ | 10 | 14128 | 68 | | :arrow_up:30 | 51 | [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 | 10 | 18410 | 69 | | :arrow_down:20 | 52 | [dlib](https://github.com/davisking/dlib) | A toolkit for making real world machine learning and data analysis applications in C++ | C++ | 10 | 4537 | 70 | | :arrow_down:11 | 53 | [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 | 10 | 12067 | 71 | | :arrow_up:16 | 54 | [turicreate](https://github.com/apple/turicreate) | Turi Create simplifies the development of custom machine learning models. | C++ | 10 | 6257 | 72 | | :arrow_up:39 | 55 | [pix2pixHD](https://github.com/NVIDIA/pix2pixHD) | Synthesizing and manipulating 2048x1024 images with conditional GANs | Python | 10 | 1739 | 73 | | :arrow_up:11 | 56 | [cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai) | Essential Cheat Sheets for deep learning and machine learning researchers | None | 9 | 9215 | 74 | | :arrow_down:5 | 57 | [imgaug](https://github.com/aleju/imgaug) | Image augmentation for machine learning experiments. | Python | 9 | 2308 | 75 | | :arrow_down:15 | 58 | [awesome-datascience](https://github.com/bulutyazilim/awesome-datascience) | :memo: An awesome Data Science repository to learn and apply for real world problems. | None | 9 | 7591 | 76 | | :new: | 59 | [pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) | Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more) | Python | 9 | 3630 | 77 | | :arrow_up:23 | 60 | [opencv4nodejs](https://github.com/justadudewhohacks/opencv4nodejs) | Asynchronous OpenCV 3.x nodejs bindings with JavaScript and TypeScript API, with examples for: Face Detection, Machine Learning, Deep Neural Nets, Hand Gesture Recognition, Object Tracking, Feature Matching, Image Histogram | C++ | 9 | 1142 | 78 | | :arrow_up:12 | 61 | [tflearn](https://github.com/tflearn/tflearn) | Deep learning library featuring a higher-level API for TensorFlow. | Python | 9 | 7825 | 79 | | :arrow_up:14 | 62 | [onnx](https://github.com/onnx/onnx) | Open Neural Network Exchange | PureBasic | 9 | 2977 | 80 | | :arrow_down:14 | 63 | [deep-learning-models](https://github.com/fchollet/deep-learning-models) | Keras code and weights files for popular deep learning models. | Python | 8 | 3249 | 81 | | :new: | 64 | [machine-learning-mindmap](https://github.com/dformoso/machine-learning-mindmap) | A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning. | None | 8 | 3266 | 82 | | :new: | 65 | [openface](https://github.com/cmusatyalab/openface) | Face recognition with deep neural networks. | Lua | 8 | 9525 | 83 | | :new: | 66 | [benchmark_results](https://github.com/foolwood/benchmark_results) | visual tracker benchmark results | None | 8 | 949 | 84 | | :arrow_down:17 | 67 | [Qix](https://github.com/ty4z2008/Qix) | Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang | None | 8 | 10840 | 85 | | :arrow_up:3 | 68 | [text_classification](https://github.com/brightmart/text_classification) | all kinds of text classificaiton models and more with deep learning | Python | 8 | 1590 | 86 | | :new: | 69 | [chainer](https://github.com/chainer/chainer) | A flexible framework of neural networks for deep learning | Python | 8 | 3623 | 87 | | :new: | 70 | [MachineLearning](https://github.com/wepe/MachineLearning) | Basic Machine Learning and Deep Learning | Python | 8 | 2370 | 88 | | :arrow_down:38 | 71 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) | A curated list of deep learning resources for computer vision | None | 8 | 6341 | 89 | | :arrow_down:25 | 72 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 8 | 6229 | 90 | | :new: | 73 | [tensorpack](https://github.com/ppwwyyxx/tensorpack) | A Neural Net Training Interface on TensorFlow | Python | 8 | 2006 | 91 | | :new: | 74 | [carla](https://github.com/carla-simulator/carla) | Open-source simulator for autonomous driving research. | C++ | 8 | 1049 | 92 | | :arrow_down:46 | 75 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 8 | 3849 | 93 | | :arrow_down:38 | 76 | [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 | 7 | 2377 | 94 | | :arrow_down:15 | 77 | [horovod](https://github.com/uber/horovod) | Distributed training framework for TensorFlow. | C++ | 7 | 1846 | 95 | | :arrow_down:9 | 78 | [Paddle](https://github.com/PaddlePaddle/Paddle) | PArallel Distributed Deep LEarning | C++ | 7 | 6622 | 96 | | :new: | 79 | [fast-style-transfer](https://github.com/lengstrom/fast-style-transfer) | TensorFlow CNN for fast style transfer! ⚡🖥🎨🖼 | Python | 7 | 5700 | 97 | | :new: | 80 | [machine_learning_examples](https://github.com/lazyprogrammer/machine_learning_examples) | A collection of machine learning examples and tutorials. | Python | 7 | 1353 | 98 | | :arrow_up:7 | 81 | [text-classification-cnn-rnn](https://github.com/gaussic/text-classification-cnn-rnn) | CNN-RNN中文文本分类，基于tensorflow | Python | 7 | 480 | 99 | | :arrow_up:8 | 82 | [mlpack](https://github.com/mlpack/mlpack) | mlpack: a scalable C++ machine learning library -- | C++ | 7 | 2090 | 100 | | :new: | 83 | [VisualDL](https://github.com/PaddlePaddle/VisualDL) | A platform to visualize the deep learning process. | Vue | 7 | 1351 | 101 | | :new: | 84 | [deep-review](https://github.com/greenelab/deep-review) | A collaboratively written review paper on deep learning, genomics, and precision medicine | CSS | 7 | 528 | 102 | | :new: | 85 | [tbd-nets](https://github.com/davidmascharka/tbd-nets) | PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning" | Jupyter Notebook | 7 | 186 | 103 | | :arrow_down:4 | 86 | [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 | 7 | 6507 | 104 | | :arrow_down:27 | 87 | [convnetjs](https://github.com/karpathy/convnetjs) | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser. | JavaScript | 7 | 8937 | 105 | | :arrow_down:3 | 88 | [tensorflow_poems](https://github.com/jinfagang/tensorflow_poems) | 中文古诗自动作诗机器人，屌炸天，基于tensorflow1.4 api，正在积极维护升级中，快star，保持更新！ | Python | 6 | 1448 | 106 | | :new: | 89 | [tvm](https://github.com/dmlc/tvm) | bring deep learning workloads to bare metal | C++ | 6 | 1298 | 107 | | :new: | 90 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 6 | 1579 | 108 | | :arrow_down:25 | 91 | [tf-pose-estimation](https://github.com/ildoonet/tf-pose-estimation) | Deep Pose Estimation implemented using Tensorflow with Custom Architecture for fast inference. | PureBasic | 6 | 601 | 109 | | :new: | 92 | [pix2pix](https://github.com/phillipi/pix2pix) | Image-to-image translation with conditional adversarial nets | Lua | 6 | 4559 | 110 | | :new: | 93 | [keras-attention-mechanism](https://github.com/philipperemy/keras-attention-mechanism) | Attention mechanism Implementation for Keras. | Python | 6 | 535 | 111 | | :arrow_down:26 | 94 | [amazon-sagemaker-examples](https://github.com/awslabs/amazon-sagemaker-examples) | Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker | Jupyter Notebook | 6 | 348 | 112 | | :new: | 95 | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | Dive into Machine Learning with Python Jupyter notebook and scikit-learn! | None | 6 | 8006 | 113 | | :new: | 96 | [neural-enhance](https://github.com/alexjc/neural-enhance) | Super Resolution for images using deep learning. | Python | 6 | 7896 | 114 | | :new: | 97 | [ai-deadlines](https://github.com/abhshkdz/ai-deadlines) | :alarm_clock: AI conference deadline countdowns | HTML | 5 | 505 | 115 | | :new: | 98 | [fastai_deeplearn_part1](https://github.com/reshamas/fastai_deeplearn_part1) | Notes for Fastai Deep Learning Course - Part 1 v2 | Jupyter Notebook | 5 | 362 | 116 | | :new: | 99 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 5 | 1322 | 117 | | :new: | 100 | [ngraph](https://github.com/NervanaSystems/ngraph) | nGraph is an open source C++ library, compiler and runtime for Deep Learning frameworks | C++ | 5 | 329 | -------------------------------------------------------------------------------- /Old-lists/04-03-2018.md: -------------------------------------------------------------------------------- 1 | # Trending deep learning Github repositories 2 | 3 | Here's a list of top 100 deep learning Github trending repositories sorted by the number of stars gained on a specific day. The query that has been used with Github search API is: 4 | 5 | - `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"` 6 | 7 | Repositories with 50000 or more are excluded. 8 | 9 | Top deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning). 10 | 11 | Date: 04-03-2018 compared to 03-31-2018 12 | 13 | Hint: This will be updated regularly. 14 | 15 | 16 | | | Pos1 | Name | Description | Language | Stars Today | Total Stars | 17 | |--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------| 18 | | :heavy_minus_sign: | 1 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated, browser based JavaScript library for training and deploying ML models. | JavaScript | 743 | 3078 | 19 | | :arrow_up:5 | 2 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 118 | 13540 | 20 | | :new: | 3 | [t81_558_deep_learning](https://github.com/jeffheaton/t81_558_deep_learning) | Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks | Jupyter Notebook | 98 | 336 | 21 | | :arrow_up:25 | 4 | [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 | 72 | 891 | 22 | | :arrow_down:2 | 5 | [tfjs-core](https://github.com/tensorflow/tfjs-core) | WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. | TypeScript | 54 | 7111 | 23 | | :arrow_down:2 | 6 | [keras](https://github.com/keras-team/keras) | Deep Learning for humans | Python | 44 | 27744 | 24 | | :arrow_down:2 | 7 | [opencv](https://github.com/opencv/opencv) | Open Source Computer Vision Library | C++ | 36 | 23441 | 25 | | :arrow_up:14 | 8 | [caffe2](https://github.com/caffe2/caffe2) | Caffe2 is a lightweight, modular, and scalable deep learning framework. | C++ | 36 | 7746 | 26 | | :arrow_down:1 | 9 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 33 | 6852 | 27 | | :heavy_minus_sign: | 10 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners with Latest APIs | Jupyter Notebook | 31 | 21156 | 28 | | :arrow_up:4 | 11 | [matchbox](https://github.com/salesforce/matchbox) | Write PyTorch code at the level of individual examples, then run it efficiently on minibatches. | Python | 27 | 317 | 29 | | :arrow_up:41 | 12 | [FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle) | Style transfer, deep learning, feature transform | Python | 26 | 7914 | 30 | | :arrow_up:17 | 13 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 26 | 5107 | 31 | | :arrow_down:1 | 14 | [Detectron](https://github.com/facebookresearch/Detectron) | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | Python | 23 | 13181 | 32 | | :arrow_down:9 | 15 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Jupyter Notebook | 23 | 4705 | 33 | | :arrow_down:14 | 16 | [Augmentor](https://github.com/mdbloice/Augmentor) | Image augmentation library in Python for machine learning. | Python | 19 | 1407 | 34 | | :arrow_down:1 | 17 | [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 | 18 | 13544 | 35 | | :arrow_down:7 | 18 | [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) | OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation | C++ | 17 | 6525 | 36 | | :heavy_minus_sign: | 19 | [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 | 16 | 6639 | 37 | | :arrow_up:4 | 20 | [DeepLearningFrameworks](https://github.com/ilkarman/DeepLearningFrameworks) | Demo of running NNs across different frameworks | Jupyter Notebook | 16 | 1064 | 38 | | :arrow_down:3 | 21 | [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 | 16 | 5693 | 39 | | :arrow_down:2 | 22 | [Personae](https://github.com/Ceruleanacg/Personae) | Personae is a repo of implements and enviorment of Deep Reinforcement Learning & Supervised Learning. | Python | 16 | 265 | 40 | | :new: | 23 | [text_classification](https://github.com/brightmart/text_classification) | all kinds of text classificaiton models and more with deep learning | Python | 16 | 1641 | 41 | | :arrow_down:12 | 24 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 16 | 16832 | 42 | | :arrow_down:11 | 25 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 15 | 23524 | 43 | | :arrow_up:9 | 26 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents | C# | 15 | 2579 | 44 | | :arrow_up:1 | 27 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 14 | 3903 | 45 | | :arrow_up:23 | 28 | [pix2code](https://github.com/tonybeltramelli/pix2code) | pix2code: Generating Code from a Graphical User Interface Screenshot | Python | 14 | 8855 | 46 | | :arrow_up:12 | 29 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) | The most cited deep learning papers | TeX | 14 | 14248 | 47 | | :new: | 30 | [TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials) | TensorFlow Tutorials with YouTube Videos | Jupyter Notebook | 14 | 3753 | 48 | | :arrow_up:2 | 31 | [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 | 14 | 12117 | 49 | | :arrow_down:11 | 32 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 13 | 6266 | 50 | | :arrow_up:25 | 33 | [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 | 13 | 3085 | 51 | | :arrow_up:33 | 34 | [Screenshot-to-code-in-Keras](https://github.com/emilwallner/Screenshot-to-code-in-Keras) | A neural network that transforms a screenshot into a static website | Jupyter Notebook | 13 | 9989 | 52 | | :arrow_down:8 | 35 | [awesome-nlp](https://github.com/keon/awesome-nlp) | :book: A curated list of resources dedicated to Natural Language Processing (NLP) | None | 12 | 4561 | 53 | | :arrow_up:18 | 36 | [fast-style-transfer](https://github.com/lengstrom/fast-style-transfer) | TensorFlow CNN for fast style transfer! ⚡🖥🎨🖼 | Python | 12 | 5739 | 54 | | :new: | 37 | [Netron](https://github.com/lutzroeder/Netron) | Visualizer for deep learning and machine learning models | JavaScript | 12 | 601 | 55 | | :arrow_up:18 | 38 | [imgaug](https://github.com/aleju/imgaug) | Image augmentation for machine learning experiments. | Python | 11 | 2344 | 56 | | :arrow_up:48 | 39 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 11 | 8816 | 57 | | :new: | 40 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 11 | 8362 | 58 | | :arrow_up:7 | 41 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) | Curated list of Machine Learning, NLP, Vision Project Ideas | None | 10 | 523 | 59 | | :new: | 42 | [mlpack](https://github.com/mlpack/mlpack) | mlpack: a scalable C++ machine learning library -- | C++ | 10 | 2106 | 60 | | :arrow_down:18 | 43 | [RL-Adventure](https://github.com/higgsfield/RL-Adventure) | Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code. | Jupyter Notebook | 10 | 708 | 61 | | :arrow_down:2 | 44 | [CNTK](https://github.com/Microsoft/CNTK) | Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit | C++ | 10 | 14159 | 62 | | :arrow_up:38 | 45 | [Tensorflow-Tutorial](https://github.com/MorvanZhou/Tensorflow-Tutorial) | Tensorflow tutorial from basic to hard | Python | 10 | 1339 | 63 | | :new: | 46 | [cheatsheets-ai](https://github.com/kailashahirwar/cheatsheets-ai) | Essential Cheat Sheets for deep learning and machine learning researchers | None | 10 | 9239 | 64 | | :new: | 47 | [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 | 9 | 3960 | 65 | | :arrow_down:22 | 48 | [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 | 9 | 18452 | 66 | | :arrow_down:12 | 49 | [allennlp](https://github.com/allenai/allennlp) | An open-source NLP research library, built on PyTorch. | Python | 9 | 1827 | 67 | | :arrow_up:13 | 50 | [keras-rl](https://github.com/keras-rl/keras-rl) | Deep Reinforcement Learning for Keras. | Python | 9 | 2381 | 68 | | :arrow_down:19 | 51 | [pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) | Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more) | Python | 9 | 3670 | 69 | | :arrow_down:5 | 52 | [ray](https://github.com/ray-project/ray) | A high-performance distributed execution engine | Python | 9 | 2900 | 70 | | :arrow_down:19 | 53 | [DeepLearning.ai-Summary](https://github.com/mbadry1/DeepLearning.ai-Summary) | This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too. | Python | 9 | 616 | 71 | | :arrow_down:37 | 54 | [keras-js](https://github.com/transcranial/keras-js) | Run Keras models in the browser, with GPU support using WebGL | JavaScript | 9 | 3868 | 72 | | :new: | 55 | [fashion-mnist](https://github.com/zalandoresearch/fashion-mnist) | A MNIST-like fashion product database. Benchmark :point_right: | Python | 8 | 3221 | 73 | | :arrow_up:13 | 56 | [char-rnn](https://github.com/karpathy/char-rnn) | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch | Lua | 8 | 7711 | 74 | | :arrow_down:11 | 57 | [onnx](https://github.com/onnx/onnx) | Open Neural Network Exchange | PureBasic | 8 | 3024 | 75 | | :arrow_up:23 | 58 | [cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf) | Convolutional Neural Network for Text Classification in Tensorflow | Python | 8 | 3007 | 76 | | :arrow_down:10 | 59 | [labelImg](https://github.com/tzutalin/labelImg) | :metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 8 | 2809 | 77 | | :new: | 60 | [tensorflow_poems](https://github.com/jinfagang/tensorflow_poems) | 中文古诗自动作诗机器人，屌炸天，基于tensorflow1.4 api，正在积极维护升级中，快star，保持更新！ | Python | 8 | 1465 | 78 | | :arrow_up:9 | 61 | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | Dive into Machine Learning with Python Jupyter notebook and scikit-learn! | None | 8 | 8029 | 79 | | :arrow_up:18 | 62 | [labelme](https://github.com/wkentaro/labelme) | Image Polygonal Annotation with Python. | Python | 7 | 515 | 80 | | :arrow_up:27 | 63 | [benchmark_results](https://github.com/foolwood/benchmark_results) | visual tracker benchmark results | None | 7 | 981 | 81 | | :arrow_up:28 | 64 | [tensorlayer](https://github.com/tensorlayer/tensorlayer) | TensorLayer: A Deep Learning and Reinforcement Learning Library for Researchers and Engineers. | Python | 7 | 3533 | 82 | | :new: | 65 | [EffectiveTensorflow](https://github.com/vahidk/EffectiveTensorflow) | TensorFlow tutorials and best practices. | None | 7 | 7092 | 83 | | :new: | 66 | [mxnet-the-straight-dope](https://github.com/zackchase/mxnet-the-straight-dope) | An interactive book on deep learning. Much easy, so MXNet. Wow. | Jupyter Notebook | 7 | 1714 | 84 | | :arrow_up:1 | 67 | [Qix](https://github.com/ty4z2008/Qix) | Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang | None | 7 | 10877 | 85 | | :new: | 68 | [dlib](https://github.com/davisking/dlib) | A toolkit for making real world machine learning and data analysis applications in C++ | C++ | 7 | 4575 | 86 | | :new: | 69 | [fast-pixel-cnn](https://github.com/PrajitR/fast-pixel-cnn) | Speed up PixelCNN++ image generation by up to a 183 times | Python | 7 | 373 | 87 | | :arrow_down:61 | 70 | [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 | 7 | 16589 | 88 | | :arrow_up:8 | 71 | [ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch) | Machine Learning From Scratch. Bare bones Python implementations of Machine Learning models and algorithms with a focus on transparency and accessibility. Aims to cover everything from Data Mining to Deep Learning. | Python | 7 | 8064 | 89 | | :new: | 72 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) | A curated list of deep learning resources for computer vision | None | 7 | 6371 | 90 | | :new: | 73 | [face-alignment](https://github.com/1adrianb/face-alignment) | :fire: 2D and 3D Face alignment library build using pytorch | Python | 6 | 1444 | 91 | | :new: | 74 | [openface](https://github.com/cmusatyalab/openface) | Face recognition with deep neural networks. | Lua | 6 | 9554 | 92 | | :new: | 75 | [tensorflow_cookbook](https://github.com/nfmcclure/tensorflow_cookbook) | Code for Tensorflow Machine Learning Cookbook | Jupyter Notebook | 6 | 2895 | 93 | | :arrow_down:3 | 76 | [tf-pose-estimation](https://github.com/ildoonet/tf-pose-estimation) | Deep Pose Estimation implemented using Tensorflow with Custom Architecture for fast inference. | PureBasic | 6 | 626 | 94 | | :arrow_down:1 | 77 | [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 | 6 | 2515 | 95 | | :arrow_down:33 | 78 | [deep-learning-models](https://github.com/fchollet/deep-learning-models) | Keras code and weights files for popular deep learning models. | Python | 6 | 3281 | 96 | | :new: | 79 | [TensorFlow-Tutorials](https://github.com/golbin/TensorFlow-Tutorials) | 텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다 | Python | 6 | 1278 | 97 | | :new: | 80 | [conv_arithmetic](https://github.com/vdumoulin/conv_arithmetic) | A technical report on convolution arithmetic in the context of deep learning | TeX | 6 | 3385 | 98 | | :new: | 81 | [text-classification-cnn-rnn](https://github.com/gaussic/text-classification-cnn-rnn) | CNN-RNN中文文本分类，基于tensorflow | Python | 6 | 493 | 99 | | :arrow_down:46 | 82 | [fastai](https://github.com/fastai/fastai) | The fast.ai deep learning library, lessons, and tutorials | Jupyter Notebook | 6 | 3865 | 100 | | :new: | 83 | [awesome-rnn](https://github.com/kjw0612/awesome-rnn) | Recurrent Neural Network - A curated list of resources dedicated to RNN | None | 6 | 4662 | 101 | | :new: | 84 | [Sign-Language](https://github.com/EvilPort2/Sign-Language) | A very simple CNN project. | Python | 6 | 406 | 102 | | :new: | 85 | [awesome-datascience](https://github.com/bulutyazilim/awesome-datascience) | :memo: An awesome Data Science repository to learn and apply for real world problems. | None | 6 | 7610 | 103 | | :new: | 86 | [DeepLearningFlappyBird](https://github.com/yenchenlin/DeepLearningFlappyBird) | Flappy Bird hack using Deep Reinforcement Learning (Deep Q-learning). | Python | 6 | 4168 | 104 | | :arrow_down:15 | 87 | [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 | 6 | 6540 | 105 | | :new: | 88 | [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 and CoreML. | Python | 6 | 1235 | 106 | | :new: | 89 | [fast-rcnn](https://github.com/rbgirshick/fast-rcnn) | Fast R-CNN | Python | 5 | 1852 | 107 | | :new: | 90 | [Meta-Learning-Papers](https://github.com/floodsung/Meta-Learning-Papers) | Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning | None | 5 | 504 | 108 | | :arrow_down:17 | 91 | [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 | 5 | 2690 | 109 | | :new: | 92 | [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 | 5 | 2228 | 110 | | :new: | 93 | [Practical_RL](https://github.com/yandexdataschool/Practical_RL) | A course in reinforcement learning in the wild | Jupyter Notebook | 5 | 1780 | 111 | | :arrow_down:54 | 94 | [tensorpack](https://github.com/ppwwyyxx/tensorpack) | A Neural Net Training Interface on TensorFlow | Python | 5 | 2032 | 112 | | :arrow_down:64 | 95 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 5 | 1624 | 113 | | :new: | 96 | [AutonomousDrivingCookbook](https://github.com/Microsoft/AutonomousDrivingCookbook) | Scenarios, tutorials and demos for Autonomous Driving | Jupyter Notebook | 5 | 888 | 114 | | :arrow_down:22 | 97 | [pytorch-book](https://github.com/chenyuntc/pytorch-book) | PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation | Jupyter Notebook | 5 | 832 | 115 | | :new: | 98 | [Paddle](https://github.com/PaddlePaddle/Paddle) | PArallel Distributed Deep LEarning | C++ | 5 | 6641 | 116 | | :new: | 99 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 5 | 1348 | 117 | | :new: | 100 | [faster_rcnn](https://github.com/ShaoqingRen/faster_rcnn) | Faster R-CNN | Matlab | 5 | 1551 | -------------------------------------------------------------------------------- /Old-lists/04-05-2018.md: -------------------------------------------------------------------------------- 1 | # Trending deep learning Github repositories 2 | 3 | Here's a list of top 100 deep learning Github trending repositories sorted by the number of stars gained on a specific day. The query that has been used with Github search API is: 4 | 5 | - `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"` 6 | 7 | Repositories with 50000 or more are excluded. 8 | 9 | Top deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning). 10 | 11 | Date: 04-05-2018 compared to 04-03-2018 12 | 13 | Hint: This will be updated regularly. 14 | 15 | 16 | | | Pos1 | Name | Description | Language | Stars Today | Total Stars | 17 | |--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------| 18 | | :heavy_minus_sign: | 1 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated, browser based JavaScript library for training and deploying ML models. | JavaScript | 218 | 4511 | 19 | | :arrow_up:33 | 2 | [awesome-nlp](https://github.com/keon/awesome-nlp) | :book: A curated list of resources dedicated to Natural Language Processing (NLP) | None | 39 | 4699 | 20 | | :arrow_up:3 | 3 | [keras](https://github.com/keras-team/keras) | Deep Learning for humans | Python | 32 | 27876 | 21 | | :arrow_down:2 | 4 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 27 | 13719 | 22 | | :arrow_up:2 | 5 | [opencv](https://github.com/opencv/opencv) | Open Source Computer Vision Library | C++ | 26 | 23513 | 23 | | :arrow_up:4 | 6 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners with Latest APIs | Jupyter Notebook | 25 | 21227 | 24 | | :arrow_up:2 | 7 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 21 | 6936 | 25 | | :arrow_up:7 | 8 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Jupyter Notebook | 19 | 4772 | 26 | | :arrow_up:61 | 9 | [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 | 18 | 16634 | 27 | | :new: | 10 | [carla](https://github.com/carla-simulator/carla) | Open-source simulator for autonomous driving research. | C++ | 16 | 1095 | 28 | | :arrow_up:3 | 11 | [Detectron](https://github.com/facebookresearch/Detectron) | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | Python | 16 | 13253 | 29 | | :arrow_up:7 | 12 | [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 | 15 | 6684 | 30 | | :arrow_up:13 | 13 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents | C# | 15 | 2616 | 31 | | :arrow_up:2 | 14 | [Augmentor](https://github.com/mdbloice/Augmentor) | Image augmentation library in Python for machine learning. | Python | 14 | 1465 | 32 | | :arrow_up:2 | 15 | [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 | 14 | 13583 | 33 | | :arrow_up:66 | 16 | [fastai](https://github.com/fastai/fastai) | The fast.ai deep learning library, lessons, and tutorials | Jupyter Notebook | 13 | 3893 | 34 | | :arrow_up:7 | 17 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 13 | 16882 | 35 | | :new: | 18 | [OpenNMT-py](https://github.com/OpenNMT/OpenNMT-py) | Open Source Neural Machine Translation in PyTorch | Python | 13 | 1182 | 36 | | :arrow_up:29 | 19 | [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 | 13 | 18485 | 37 | | :arrow_up:5 | 20 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 13 | 23562 | 38 | | :heavy_minus_sign: | 21 | [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 | 12 | 5724 | 39 | | :arrow_up:7 | 22 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) | The most cited deep learning papers | TeX | 12 | 14292 | 40 | | :arrow_up:10 | 23 | [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 | 12 | 3108 | 41 | | :new: | 24 | [indrnn](https://github.com/batzner/indrnn) | TensorFlow implementation of Independently Recurrent Neural Networks | Python | 12 | 264 | 42 | | :new: | 25 | [neural-enhance](https://github.com/alexjc/neural-enhance) | Super Resolution for images using deep learning. | Python | 12 | 7933 | 43 | | :arrow_up:4 | 26 | [TensorFlow-Tutorials](https://github.com/Hvass-Labs/TensorFlow-Tutorials) | TensorFlow Tutorials with YouTube Videos | Jupyter Notebook | 11 | 3780 | 44 | | :arrow_down:22 | 27 | [tfjs-core](https://github.com/tensorflow/tfjs-core) | WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. | TypeScript | 11 | 7170 | 45 | | :new: | 28 | [Awesome-TensorFlow-Chinese](https://github.com/fendouai/Awesome-TensorFlow-Chinese) | 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：522785813，微信群二维码：http://www.tensorflownews.com/ | Python | 10 | 669 | 46 | | :new: | 29 | [deep-learning-with-keras-notebooks](https://github.com/erhwenkuo/deep-learning-with-keras-notebooks) | Jupyter notebooks for using & learning Keras | Jupyter Notebook | 10 | 350 | 47 | | :arrow_up:57 | 30 | [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 | 10 | 6557 | 48 | | :arrow_up:41 | 31 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) | A curated list of deep learning resources for computer vision | None | 10 | 6394 | 49 | | :new: | 32 | [CycleGAN](https://github.com/junyanz/CycleGAN) | Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more. | Lua | 10 | 6074 | 50 | | :arrow_down:15 | 33 | [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) | OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation | C++ | 9 | 6567 | 51 | | :arrow_down:7 | 34 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 9 | 3944 | 52 | | :arrow_up:19 | 35 | [keras-js](https://github.com/transcranial/keras-js) | Run Keras models in the browser, with GPU support using WebGL | JavaScript | 9 | 3901 | 53 | | :arrow_up:1 | 36 | [Netron](https://github.com/lutzroeder/Netron) | Visualizer for deep learning and machine learning models | JavaScript | 9 | 626 | 54 | | :arrow_down:33 | 37 | [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 | 9 | 968 | 55 | | :heavy_minus_sign: | 38 | [imgaug](https://github.com/aleju/imgaug) | Image augmentation for machine learning experiments. | Python | 9 | 2372 | 56 | | :arrow_up:22 | 39 | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | Dive into Machine Learning with Python Jupyter notebook and scikit-learn! | None | 9 | 8045 | 57 | | :new: | 40 | [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | Deep Learning for Java, Scala & Clojure on Hadoop & Spark With GPUs - From Skymind | Java | 8 | 8628 | 58 | | :arrow_down:7 | 41 | [Screenshot-to-code-in-Keras](https://github.com/emilwallner/Screenshot-to-code-in-Keras) | A neural network that transforms a screenshot into a static website | Jupyter Notebook | 8 | 10016 | 59 | | :arrow_up:32 | 42 | [openface](https://github.com/cmusatyalab/openface) | Face recognition with deep neural networks. | Lua | 8 | 9583 | 60 | | :arrow_up:45 | 43 | [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 and CoreML. | Python | 8 | 1256 | 61 | | :heavy_minus_sign: | 44 | [CNTK](https://github.com/Microsoft/CNTK) | Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit | C++ | 8 | 14177 | 62 | | :new: | 45 | [lectures](https://github.com/oxford-cs-deepnlp-2017/lectures) | Oxford Deep NLP 2017 course | None | 8 | 11566 | 63 | | :arrow_down:14 | 46 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 8 | 6294 | 64 | | :arrow_up:38 | 47 | [awesome-datascience](https://github.com/bulutyazilim/awesome-datascience) | :memo: An awesome Data Science repository to learn and apply for real world problems. | None | 8 | 7627 | 65 | | :new: | 48 | [tf-rnn](https://github.com/dennybritz/tf-rnn) | Practical Examples for RNNs in Tensorflow | Jupyter Notebook | 7 | 409 | 66 | | :new: | 49 | [turicreate](https://github.com/apple/turicreate) | Turi Create simplifies the development of custom machine learning models. | C++ | 7 | 6294 | 67 | | :arrow_up:29 | 50 | [TensorFlow-Tutorials](https://github.com/golbin/TensorFlow-Tutorials) | 텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다 | Python | 7 | 1285 | 68 | | :arrow_down:6 | 51 | [Tensorflow-Tutorial](https://github.com/MorvanZhou/Tensorflow-Tutorial) | Tensorflow tutorial from basic to hard | Python | 7 | 1362 | 69 | | :arrow_up:39 | 52 | [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 | 7 | 2709 | 70 | | :arrow_up:4 | 53 | [onnx](https://github.com/onnx/onnx) | Open Neural Network Exchange | PureBasic | 6 | 3047 | 71 | | :arrow_up:4 | 54 | [cnn-text-classification-tf](https://github.com/dennybritz/cnn-text-classification-tf) | Convolutional Neural Network for Text Classification in Tensorflow | Python | 6 | 3022 | 72 | | :arrow_down:3 | 55 | [ray](https://github.com/ray-project/ray) | A high-performance distributed execution engine | Python | 6 | 2919 | 73 | | :new: | 56 | [deep-learning-keras-tensorflow](https://github.com/leriomaggio/deep-learning-keras-tensorflow) | Introduction to Deep Neural Networks with Keras and Tensorflow | Jupyter Notebook | 6 | 1933 | 74 | | :new: | 57 | [DeblurGAN](https://github.com/KupynOrest/DeblurGAN) | Image Deblurring using Generative Adversarial Networks | Python | 6 | 741 | 75 | | :new: | 58 | [deeplearning-papernotes](https://github.com/dennybritz/deeplearning-papernotes) | Summaries and notes on Deep Learning research papers | None | 6 | 3231 | 76 | | :new: | 59 | [edward](https://github.com/blei-lab/edward) | A probabilistic programming language in TensorFlow. Deep generative models, variational inference. | Jupyter Notebook | 6 | 3441 | 77 | | :arrow_down:10 | 60 | [keras-rl](https://github.com/keras-rl/keras-rl) | Deep Reinforcement Learning for Keras. | Python | 6 | 2395 | 78 | | :arrow_down:2 | 61 | [labelImg](https://github.com/tzutalin/labelImg) | :metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 6 | 2880 | 79 | | :arrow_up:35 | 62 | [pytorch-book](https://github.com/chenyuntc/pytorch-book) | PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation | Jupyter Notebook | 6 | 855 | 80 | | :new: | 63 | [pointnet](https://github.com/charlesq34/pointnet) | PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation | Python | 6 | 802 | 81 | | :new: | 64 | [keras-rcnn](https://github.com/broadinstitute/keras-rcnn) | Keras package for region-based convolutional neural networks (RCNNs) | Python | 6 | 288 | 82 | | :arrow_down:52 | 65 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 6 | 5141 | 83 | | :arrow_down:26 | 66 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 6 | 8382 | 84 | | :new: | 67 | [tflearn](https://github.com/tflearn/tflearn) | Deep learning library featuring a higher-level API for TensorFlow. | Python | 6 | 7869 | 85 | | :new: | 68 | [opencv4nodejs](https://github.com/justadudewhohacks/opencv4nodejs) | Asynchronous OpenCV 3.x nodejs bindings with JavaScript and TypeScript API, with examples for: Face Detection, Machine Learning, Deep Neural Nets, Hand Gesture Recognition, Object Tracking, Feature Matching, Image Histogram | C++ | 5 | 1177 | 86 | | :new: | 69 | [DeepLearningZeroToAll](https://github.com/hunkim/DeepLearningZeroToAll) | TensorFlow Basic Tutorial Labs | Jupyter Notebook | 5 | 2249 | 87 | | :arrow_down:28 | 70 | [mlpack](https://github.com/mlpack/mlpack) | mlpack: a scalable C++ machine learning library -- | C++ | 5 | 2128 | 88 | | :new: | 71 | [simplified-deeplearning](https://github.com/exacity/simplified-deeplearning) | Simplified implementations of deep learning related works | Jupyter Notebook | 5 | 1501 | 89 | | :arrow_down:41 | 72 | [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 | 5 | 12136 | 90 | | :new: | 73 | [quiver](https://github.com/keplr-io/quiver) | Interactive convnet features visualization for Keras | JavaScript | 5 | 1265 | 91 | | :new: | 74 | [luminoth](https://github.com/tryolabs/luminoth) | Deep Learning toolkit for Computer Vision | Python | 5 | 1395 | 92 | | :new: | 75 | [jetson-reinforcement](https://github.com/dusty-nv/jetson-reinforcement) | Deep reinforcement learning libraries for NVIDIA Jetson TX1/TX2 with PyTorch, OpenAI Gym, and Gazebo robotics simulator. | C++ | 5 | 188 | 93 | | :new: | 76 | [pix2pix](https://github.com/phillipi/pix2pix) | Image-to-image translation with conditional adversarial nets | Lua | 5 | 4583 | 94 | | :new: | 77 | [gorgonia](https://github.com/gorgonia/gorgonia) | Gorgonia is a library that helps facilitate machine learning in Go. | Go | 5 | 1788 | 95 | | :new: | 78 | [deep-residual-networks](https://github.com/KaimingHe/deep-residual-networks) | Deep Residual Learning for Image Recognition | None | 5 | 3529 | 96 | | :new: | 79 | [char-rnn-tensorflow](https://github.com/sherjilozair/char-rnn-tensorflow) | Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow | Python | 5 | 1895 | 97 | | :new: | 80 | [cnn-benchmarks](https://github.com/jcjohnson/cnn-benchmarks) | Benchmarks for popular CNN models | Python | 5 | 1382 | 98 | | :arrow_up:14 | 81 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 5 | 1639 | 99 | | :new: | 82 | [TensorFlow-LiveLessons](https://github.com/the-deep-learners/TensorFlow-LiveLessons) | "Deep Learning with TensorFlow" LiveLessons | Jupyter Notebook | 5 | 389 | 100 | | :new: | 83 | [ssd_keras](https://github.com/pierluigiferrari/ssd_keras) | A Keras port of Single Shot MultiBox Detector | Python | 5 | 310 | 101 | | :arrow_down:41 | 84 | [RL-Adventure](https://github.com/higgsfield/RL-Adventure) | Pytorch easy-to-follow step-by-step Deep Q Learning tutorial with clean readable code. | Jupyter Notebook | 5 | 724 | 102 | | :arrow_down:36 | 85 | [allennlp](https://github.com/allenai/allennlp) | An open-source NLP research library, built on PyTorch. | Python | 5 | 1842 | 103 | | :new: | 86 | [Tensorflow-Project-Template](https://github.com/MrGemy95/Tensorflow-Project-Template) | A best practice for tensorflow project template architecture. | Python | 5 | 1796 | 104 | | :arrow_down:20 | 87 | [Qix](https://github.com/ty4z2008/Qix) | Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang | None | 4 | 10889 | 105 | | :new: | 88 | [pointnet2](https://github.com/charlesq34/pointnet2) | PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space | Python | 4 | 294 | 106 | | :arrow_down:77 | 89 | [FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle) | Style transfer, deep learning, feature transform | Python | 4 | 7954 | 107 | | :arrow_down:19 | 90 | [ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch) | Machine Learning From Scratch. Bare bones Python implementations of Machine Learning models and algorithms with a focus on transparency and accessibility. Aims to cover everything from Data Mining to Deep Learning. | Python | 4 | 8076 | 108 | | :new: | 91 | [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 | 4 | 2308 | 109 | | :new: | 92 | [keras-vis](https://github.com/raghakot/keras-vis) | Neural network visualization toolkit for keras | Python | 4 | 1354 | 110 | | :arrow_down:1 | 93 | [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 | 4 | 2238 | 111 | | :new: | 94 | [gluon-tutorials-zh](https://github.com/mli/gluon-tutorials-zh) | 通过 MXNet / Gluon 来动手学习深度学习 | Python | 4 | 2161 | 112 | | :new: | 95 | [proteinnet](https://github.com/aqlaboratory/proteinnet) | Standardized data set for machine learning of protein structure | Python | 4 | 195 | 113 | | :new: | 96 | [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 | 4 | 2449 | 114 | | :new: | 97 | [torchsample](https://github.com/ncullen93/torchsample) | High-Level Training, Data Augmentation, and Utilities for Pytorch | Python | 4 | 728 | 115 | | :new: | 98 | [ml-cheatsheet](https://github.com/bfortuner/ml-cheatsheet) | Machine learning cheatsheet | Python | 4 | 327 | 116 | | :new: | 99 | [convnetjs](https://github.com/karpathy/convnetjs) | Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser. | JavaScript | 4 | 8965 | 117 | | :new: | 100 | [PyTorch-Tutorial](https://github.com/MorvanZhou/PyTorch-Tutorial) | Build your neural network easy and fast | Jupyter Notebook | 4 | 1000 | -------------------------------------------------------------------------------- /Old-lists/04-25-2018.md: -------------------------------------------------------------------------------- 1 | # Trending deep learning Github repositories 2 | 3 | Here's a list of top 100 deep learning Github trending repositories sorted by the number of stars gained on a specific day. The query that has been used with Github search API is: 4 | 5 | - `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"` 6 | 7 | Repositories with 50000 stars or more are excluded. 8 | 9 | Top deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning). 10 | 11 | Date: 04-25-2018 compared to 04-10-2018 12 | 13 | Hint: This will be updated regularly. 14 | 15 | 16 | | | Pos1 | Name | Description | Language | Stars Today | Total Stars | 17 | |--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------| 18 | | :heavy_minus_sign: | 1 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated, browser based JavaScript library for training and deploying ML models. | JavaScript | 75 | 6292 | 19 | | :arrow_up:53 | 2 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 51 | 1520 | 20 | | :arrow_up:2 | 3 | [keras](https://github.com/keras-team/keras) | Deep Learning for humans | Python | 50 | 28668 | 21 | | :arrow_up:2 | 4 | [opencv](https://github.com/opencv/opencv) | Open Source Computer Vision Library | C++ | 48 | 24072 | 22 | | :arrow_down:1 | 5 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 45 | 14323 | 23 | | :arrow_up:6 | 6 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners with Latest APIs | Jupyter Notebook | 35 | 21821 | 24 | | :arrow_up:1 | 7 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Python | 34 | 5319 | 25 | | :new: | 8 | [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 | 34 | 1330 | 26 | | :arrow_up:4 | 9 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 30 | 17324 | 27 | | :heavy_minus_sign: | 10 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 24 | 7361 | 28 | | :arrow_up:33 | 11 | [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 | 22 | 6049 | 29 | | :arrow_up:3 | 12 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 21 | 5445 | 30 | | :arrow_up:35 | 13 | [fastai](https://github.com/fastai/fastai) | The fast.ai deep learning library, lessons, and tutorials | Jupyter Notebook | 21 | 4164 | 31 | | :arrow_up:23 | 14 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 20 | 4187 | 32 | | :arrow_down:6 | 15 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 20 | 23854 | 33 | | :arrow_up:5 | 16 | [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 | 20 | 1265 | 34 | | :new: | 17 | [probability](https://github.com/tensorflow/probability) | Probabilistic reasoning and statistical analysis in TensorFlow | Jupyter Notebook | 19 | 479 | 35 | | :arrow_down:4 | 18 | [Detectron](https://github.com/facebookresearch/Detectron) | FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet. | Python | 19 | 13620 | 36 | | :arrow_up:26 | 19 | [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 and CoreML. | Python | 19 | 1367 | 37 | | :arrow_up:12 | 20 | [tfjs-core](https://github.com/tensorflow/tfjs-core) | WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript. | TypeScript | 16 | 7376 | 38 | | :new: | 21 | [zhusuan](https://github.com/thu-ml/zhusuan) | A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow | Python | 15 | 1225 | 39 | | :new: | 22 | [DeepNLP-models-Pytorch](https://github.com/DSKSD/DeepNLP-models-Pytorch) | Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ) | Jupyter Notebook | 14 | 1186 | 40 | | :arrow_down:1 | 23 | [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 | 14 | 7020 | 41 | | :new: | 24 | [EAST](https://github.com/argman/EAST) | A tensorflow implementation of EAST text detector | C++ | 14 | 643 | 42 | | :arrow_up:5 | 25 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents | C# | 14 | 2805 | 43 | | :arrow_down:6 | 26 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 13 | 8613 | 44 | | :arrow_up:14 | 27 | [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 | 13 | 18648 | 45 | | :arrow_up:48 | 28 | [labelImg](https://github.com/tzutalin/labelImg) | :metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 13 | 3103 | 46 | | :arrow_up:22 | 29 | [dlib](https://github.com/davisking/dlib) | A toolkit for making real world machine learning and data analysis applications in C++ | C++ | 13 | 4730 | 47 | | :arrow_down:7 | 30 | [text_classification](https://github.com/brightmart/text_classification) | all kinds of text classificaiton models and more with deep learning | Python | 12 | 1804 | 48 | | :new: | 31 | [BicycleGAN](https://github.com/junyanz/BicycleGAN) | [NIPS 2017] Toward Multimodal Image-to-Image Translation | Python | 12 | 521 | 49 | | :arrow_up:46 | 32 | [ML-From-Scratch](https://github.com/eriklindernoren/ML-From-Scratch) | Machine Learning From Scratch. Bare bones Python implementations of Machine Learning models and algorithms with a focus on transparency and accessibility. Aims to cover everything from Data Mining to Deep Learning. | Python | 12 | 8152 | 50 | | :arrow_down:30 | 33 | [awesome-nlp](https://github.com/keon/awesome-nlp) | :book: A curated list of resources dedicated to Natural Language Processing (NLP) | None | 12 | 5369 | 51 | | :arrow_up:4 | 34 | [allennlp](https://github.com/allenai/allennlp) | An open-source NLP research library, built on PyTorch. | Python | 12 | 1972 | 52 | | :arrow_down:18 | 35 | [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) | OpenPose: Real-time multi-person keypoint detection library for body, face, and hands estimation | C++ | 12 | 6821 | 53 | | :arrow_up:30 | 36 | [pytorch-CycleGAN-and-pix2pix](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix) | Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more) | Python | 12 | 3855 | 54 | | :arrow_up:50 | 37 | [pix2pix](https://github.com/phillipi/pix2pix) | Image-to-image translation with conditional adversarial nets | Lua | 12 | 4669 | 55 | | :arrow_up:30 | 38 | [imgaug](https://github.com/aleju/imgaug) | Image augmentation for machine learning experiments. | Python | 11 | 2531 | 56 | | :arrow_up:32 | 39 | [openface](https://github.com/cmusatyalab/openface) | Face recognition with deep neural networks. | Lua | 11 | 9727 | 57 | | :arrow_up:10 | 40 | [tensorlayer](https://github.com/tensorlayer/tensorlayer) | TensorLayer: A Deep Learning and Reinforcement Learning Library for Researchers and Engineers. | Python | 11 | 3668 | 58 | | :arrow_down:25 | 41 | [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 | 11 | 16917 | 59 | | :arrow_down:11 | 42 | [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 | 10 | 12361 | 60 | | :arrow_up:6 | 43 | [awesome-deep-vision](https://github.com/kjw0612/awesome-deep-vision) | A curated list of deep learning resources for computer vision | None | 10 | 6527 | 61 | | :arrow_up:3 | 44 | [conv_arithmetic](https://github.com/vdumoulin/conv_arithmetic) | A technical report on convolution arithmetic in the context of deep learning | TeX | 10 | 3567 | 62 | | :new: | 45 | [MUNIT](https://github.com/NVlabs/MUNIT) | Multimodal Unsupervised Image-to-Image Translation | Python | 10 | 704 | 63 | | :arrow_down:19 | 46 | [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 | 10 | 2887 | 64 | | :arrow_down:18 | 47 | [pytorch-book](https://github.com/chenyuntc/pytorch-book) | PyTorch tutorials and fun projects including neural talk, neural style, poem writing, anime generation | Jupyter Notebook | 9 | 1000 | 65 | | :new: | 48 | [textgenrnn](https://github.com/minimaxir/textgenrnn) | Python module to easily generate text using a pretrained character-based recurrent neural network. | Python | 9 | 517 | 66 | | :new: | 49 | [faster-rcnn.pytorch](https://github.com/jwyang/faster-rcnn.pytorch) | A faster pytorch implementation of faster r-cnn | Python | 9 | 1087 | 67 | | :new: | 50 | [MTCNN_face_detection_alignment](https://github.com/kpzhang93/MTCNN_face_detection_alignment) | Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks | Matlab | 9 | 1011 | 68 | | :arrow_down:12 | 51 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 9 | 6472 | 69 | | :arrow_down:17 | 52 | [FastPhotoStyle](https://github.com/NVIDIA/FastPhotoStyle) | Style transfer, deep learning, feature transform | Python | 9 | 8100 | 70 | | :arrow_up:8 | 53 | [CycleGAN](https://github.com/junyanz/CycleGAN) | Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more. | Lua | 9 | 6205 | 71 | | :arrow_up:4 | 54 | [awesome-deep-learning-papers](https://github.com/terryum/awesome-deep-learning-papers) | The most cited deep learning papers | TeX | 9 | 14541 | 72 | | :arrow_up:33 | 55 | [Paddle](https://github.com/PaddlePaddle/Paddle) | PArallel Distributed Deep LEarning | C++ | 9 | 6786 | 73 | | :arrow_up:3 | 56 | [CNTK](https://github.com/Microsoft/CNTK) | Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit | C++ | 9 | 14298 | 74 | | :arrow_up:3 | 57 | [Augmentor](https://github.com/mdbloice/Augmentor) | Image augmentation library in Python for machine learning. | Python | 9 | 1691 | 75 | | :new: | 58 | [awesome-datascience](https://github.com/bulutyazilim/awesome-datascience) | :memo: An awesome Data Science repository to learn and apply for real world problems. | None | 9 | 7730 | 76 | | :arrow_down:41 | 59 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 9 | 9032 | 77 | | :arrow_down:27 | 60 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 8 | 1795 | 78 | | :new: | 61 | [ray](https://github.com/ray-project/ray) | A high-performance distributed execution engine | Python | 8 | 3127 | 79 | | :arrow_down:38 | 62 | [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 | 8 | 13760 | 80 | | :arrow_up:18 | 63 | [char-rnn](https://github.com/karpathy/char-rnn) | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch | Lua | 8 | 7806 | 81 | | :arrow_down:28 | 64 | [Qix](https://github.com/ty4z2008/Qix) | Machine Learning、Deep Learning、PostgreSQL、Distributed System、Node.Js、Golang | None | 8 | 11010 | 82 | | :new: | 65 | [ncnn](https://github.com/Tencent/ncnn) | ncnn is a high-performance neural network inference framework optimized for the mobile platform | C++ | 8 | 3678 | 83 | | :arrow_down:14 | 66 | [onnx](https://github.com/onnx/onnx) | Open Neural Network Exchange | PureBasic | 7 | 3174 | 84 | | :arrow_down:33 | 67 | [Screenshot-to-code-in-Keras](https://github.com/emilwallner/Screenshot-to-code-in-Keras) | A neural network that transforms a screenshot into a static website | Jupyter Notebook | 7 | 10149 | 85 | | :new: | 68 | [tflearn](https://github.com/tflearn/tflearn) | Deep learning library featuring a higher-level API for TensorFlow. | Python | 7 | 7956 | 86 | | :arrow_up:13 | 69 | [caffe2](https://github.com/caffe2/caffe2) | Caffe2 is a lightweight, modular, and scalable deep learning framework. | C++ | 7 | 7839 | 87 | | :arrow_up:30 | 70 | [Tensorflow-Project-Template](https://github.com/MrGemy95/Tensorflow-Project-Template) | A best practice for tensorflow project template architecture. | Python | 7 | 1885 | 88 | | :new: | 71 | [fashion-mnist](https://github.com/zalandoresearch/fashion-mnist) | A MNIST-like fashion product database. Benchmark :point_right: | Python | 7 | 3305 | 89 | | :new: | 72 | [tensorflow_scala](https://github.com/eaplatanios/tensorflow_scala) | TensorFlow API for the Scala Programming Language | Scala | 6 | 344 | 90 | | :arrow_up:7 | 73 | [DeepLearn](https://github.com/GauravBh1010tt/DeepLearn) | Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn. | Python | 6 | 1221 | 91 | | :new: | 74 | [awesome-deep-learning-music](https://github.com/ybayle/awesome-deep-learning-music) | List of articles related to deep learning applied to music | TeX | 6 | 491 | 92 | | :new: | 75 | [DenseNet](https://github.com/liuzhuang13/DenseNet) | Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award). | Lua | 6 | 2413 | 93 | | :new: | 76 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) | Curated list of Machine Learning, NLP, Vision Project Ideas | None | 6 | 628 | 94 | | :new: | 77 | [tensorpack](https://github.com/ppwwyyxx/tensorpack) | A Neural Net Training Interface on TensorFlow | Python | 6 | 2109 | 95 | | :new: | 78 | [tensorflow_cookbook](https://github.com/nfmcclure/tensorflow_cookbook) | Code for Tensorflow Machine Learning Cookbook | Jupyter Notebook | 6 | 3008 | 96 | | :arrow_down:12 | 79 | [SSD-Tensorflow](https://github.com/balancap/SSD-Tensorflow) | Single Shot MultiBox Detector in TensorFlow | Jupyter Notebook | 6 | 1676 | 97 | | :arrow_down:78 | 80 | [PyTorch-NLP](https://github.com/PetrochukM/PyTorch-NLP) | Supporting Rapid Prototyping with a Toolkit (incl. Datasets and Neural Network Layers) | Python | 6 | 676 | 98 | | :new: | 81 | [OpenNMT-py](https://github.com/OpenNMT/OpenNMT-py) | Open Source Neural Machine Translation in PyTorch | Python | 6 | 1277 | 99 | | :new: | 82 | [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 | 6 | 3236 | 100 | | :new: | 83 | [Keras-Project-Template](https://github.com/Ahmkel/Keras-Project-Template) | A project template to simplify building and training deep learning models using Keras. | Python | 6 | 500 | 101 | | :new: | 84 | [luminoth](https://github.com/tryolabs/luminoth) | Deep Learning toolkit for Computer Vision | Python | 6 | 1476 | 102 | | :arrow_up:11 | 85 | [ssd.pytorch](https://github.com/amdegroot/ssd.pytorch) | A PyTorch Implementation of Single Shot MultiBox Detector | Python | 6 | 768 | 103 | | :new: | 86 | [pix2code](https://github.com/tonybeltramelli/pix2code) | pix2code: Generating Code from a Graphical User Interface Screenshot | Python | 6 | 8994 | 104 | | :new: | 87 | [MachineLearning](https://github.com/allmachinelearning/MachineLearning) | Machine learning resources | None | 6 | 916 | 105 | | :new: | 88 | [fast-style-transfer](https://github.com/lengstrom/fast-style-transfer) | TensorFlow CNN for fast style transfer! ⚡🖥🎨🖼 | Python | 6 | 5893 | 106 | | :arrow_down:61 | 89 | [Machine-Learning-Tutorials](https://github.com/ujjwalkarn/Machine-Learning-Tutorials) | machine learning and deep learning tutorials, articles and other resources | None | 6 | 7193 | 107 | | :new: | 90 | [pytorch-cnn-finetune](https://github.com/creafz/pytorch-cnn-finetune) | Fine-tune pretrained Convolutional Neural Networks with PyTorch | Python | 6 | 181 | 108 | | :arrow_down:45 | 91 | [deeplearning4j](https://github.com/deeplearning4j/deeplearning4j) | Deep Learning for Java, Scala & Clojure on Hadoop & Spark With GPUs - From Skymind | Java | 6 | 8764 | 109 | | :new: | 92 | [dive-into-machine-learning](https://github.com/hangtwenty/dive-into-machine-learning) | Dive into Machine Learning with Python Jupyter notebook and scikit-learn! | None | 6 | 8127 | 110 | | :new: | 93 | [deep-learning-models](https://github.com/fchollet/deep-learning-models) | Keras code and weights files for popular deep learning models. | Python | 6 | 3396 | 111 | | :new: | 94 | [deep-learning-model-convertor](https://github.com/ysh329/deep-learning-model-convertor) | The convertor/conversion of deep learning models for different deep learning frameworks/softwares. | None | 6 | 965 | 112 | | :arrow_down:76 | 95 | [lectures](https://github.com/oxford-cs-deepnlp-2017/lectures) | Oxford Deep NLP 2017 course | None | 6 | 11704 | 113 | | :new: | 96 | [deepLearningBook-Notes](https://github.com/hadrienj/deepLearningBook-Notes) | Notes on the Deep Learning book from Ian Goodfellow, Yoshua Bengio and Aaron Courville (2016) | Jupyter Notebook | 6 | 184 | 114 | | :new: | 97 | [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 | 5 | 1070 | 115 | | :arrow_down:28 | 98 | [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 | 5 | 4089 | 116 | | :arrow_down:13 | 99 | [keras-resources](https://github.com/fchollet/keras-resources) | Directory of tutorials and open-source code repositories for working with Keras, the Python deep learning library | None | 5 | 2002 | 117 | | :new: | 100 | [tf-pose-estimation](https://github.com/ildoonet/tf-pose-estimation) | Deep Pose Estimation implemented using Tensorflow with Custom Architecture for fast inference. | PureBasic | 5 | 732 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | # Imports 2 | import numpy as np 3 | import pandas as pd 4 | from github import Github 5 | from terminaltables import AsciiTable 6 | from terminaltables import GithubFlavoredMarkdownTable 7 | import pickle 8 | import codecs 9 | import urllib.parse as urlparse # For url parsing 10 | from datetime import datetime, timedelta 11 | from IPython.display import clear_output 12 | 13 | # Functions 14 | 15 | def get_last_stargazers_page_number(stargazers): 16 | """ 17 | stargazers: List of stargazers output of pygithub package 18 | """ 19 | url = stargazers._getLastPageUrl() 20 | if url is None: 21 | return 0 22 | page_num = int(urlparse.parse_qs(urlparse.urlparse(url).query)['page'][0]) 23 | return page_num 24 | 25 | 26 | def get_stars_count_in_last_days(rep, days, print_user=True): 27 | """ 28 | rep: Object of github repository which was made by pygithub package 29 | days: int, number of last days to get the count at. 30 | """ 31 | last_stargazers_page_num = get_last_stargazers_page_number(rep.get_stargazers()) 32 | if print_user: 33 | print("Number of stargazzers:",last_stargazers_page_num) 34 | 35 | last_day = True 36 | total_count = 0 37 | for page_num in range(last_stargazers_page_num-1, -1, -1): 38 | stargazers = rep.get_stargazers_with_dates().get_page(page_num)[::-1] 39 | for star in stargazers: 40 | if datetime.now() - star.starred_at < timedelta(days=days): 41 | total_count += 1 42 | if print_user: 43 | print(star.starred_at, star.user) 44 | # print(star) 45 | else: 46 | last_day = False 47 | break 48 | 49 | if not last_day: 50 | break 51 | return total_count 52 | 53 | 54 | def pandas_table_to_nested_list(df): 55 | """ 56 | Converts pandas table df to nested list 57 | """ 58 | table_data = [["" for x in range(df.shape[1])] for y in range(df.shape[0]+1)] 59 | 60 | # Columns names 61 | for i in range(df.shape[1]): 62 | table_data[0][i] = df.columns[i] 63 | 64 | for i in range(df.shape[0]): 65 | for j in range(df.shape[1]): 66 | table_data[i+1][j] = df.iat[i, j] 67 | 68 | return table_data 69 | 70 | 71 | # Github object 72 | username = "" 73 | password = "" 74 | g = Github(username, password) 75 | 76 | # Settings 77 | query = 'deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"' 78 | number_of_reps_to_present = 100 79 | number_of_reps_to_check = 1000 80 | days_to_check = 1 81 | biggest_stars_number = 50000 # Because of github limitations! 82 | names_of_props = ["Name", "Description", "Language", "Stars Today", "Total Stars"] 83 | github_server_link = "https://github.com/" 84 | last_tables_file_name = 'last_table_data.pickle' 85 | md_file_name = 'readme.md' 86 | # Symbols 87 | new_symbol = ":new:" 88 | up_symbol = ":arrow_up:" 89 | down_symbol = ":arrow_down:" 90 | same_symbol = ":heavy_minus_sign:" 91 | 92 | # Main query 93 | df = pd.DataFrame(columns=names_of_props) 94 | df_count = 0 95 | seach_query = g.search_repositories(query, sort="stars", order="desc") 96 | results = [] 97 | for index, rep in enumerate(seach_query): 98 | 99 | # print(rep.full_name) 100 | 101 | clear_output() 102 | print(index) 103 | 104 | if rep.stargazers_count > biggest_stars_number: 105 | continue 106 | 107 | link = github_server_link + rep.full_name 108 | starts_count = get_stars_count_in_last_days(rep, days_to_check, print_user=False) 109 | 110 | lst = [] 111 | lst.append("[{}]({})".format(rep.name, link)) 112 | lst.append(rep.description) 113 | lst.append(rep.language) 114 | lst.append(starts_count) 115 | lst.append(rep.stargazers_count) 116 | 117 | df.loc[df_count] = lst 118 | df_count += 1 119 | 120 | if(index > number_of_reps_to_check-2): 121 | break 122 | 123 | # Sorting 124 | df = df.sort_values(by=["Stars Today"], ascending=False) 125 | 126 | # Slicing 127 | df = df.iloc[0:number_of_reps_to_present] 128 | 129 | # Inserting pos column 130 | df.insert(0, "Pos1", list(range(1, number_of_reps_to_present+1))) 131 | 132 | table_data = pandas_table_to_nested_list(df) 133 | 134 | # Generating the ascii table 135 | table = GithubFlavoredMarkdownTable(table_data) 136 | table_str = table.table 137 | 138 | # Wrting the md file 139 | with codecs.open(md_file_name, "w", "utf-8") as f: 140 | f.write(table_str) -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # Trending deep learning Github repositories 2 | 3 | Here's a list of top 100 deep learning Github trending repositories sorted by the number of stars gained on a specific day. The query that has been used with Github search API is: 4 | 5 | - `deep-learning OR CNN OR RNN OR "convolutional neural network" OR "recurrent neural network"` 6 | 7 | Repositories with 40000 stars or more are excluded. 8 | 9 | Top deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning). 10 | 11 | Date: 02-02-2020 compared to 09-01-2019 12 | 13 | Note: This will be updated regularly. 14 | 15 | | | Pos1 | Name | Description | Language | Stars Today | Total Stars | 16 | |--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------| 17 | | :new: | 1 | [spinningup](https://github.com/openai/spinningup) | An educational resource to help anyone learn deep reinforcement learning. | Python | 53 | 4030 | 18 | | :arrow_up:2 | 2 | [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 | 18 | 15014 | 19 | | :new: | 3 | [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 | 17 | 6771 | 20 | | :arrow_up:15 | 4 | [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 | 16 | 10248 | 21 | | :arrow_up:1 | 5 | [DeepFaceLab](https://github.com/iperov/DeepFaceLab) | DeepFaceLab is the leading software for creating deep fakes. | Python | 15 | 12237 | 22 | | :new: | 6 | [pytorch3d](https://github.com/facebookresearch/pytorch3d) | PyTorch3d is FAIR's library of reusable components for deep learning with 3D data. | Python | 15 | 544 | 23 | | :new: | 7 | [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 | 15 | 7092 | 24 | | :new: | 8 | [thinc](https://github.com/explosion/thinc) | 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries | Python | 15 | 1683 | 25 | | :arrow_up:15 | 9 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 14 | 15314 | 26 | | :arrow_up:39 | 10 | [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 | 14 | 5921 | 27 | | :arrow_up:3 | 11 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 14 | 35719 | 28 | | :arrow_up:35 | 12 | [pytorch_geometric](https://github.com/rusty1s/pytorch_geometric) | Geometric Deep Learning Extension Library for PyTorch | Python | 11 | 6473 | 29 | | :arrow_down:11 | 13 | [faceswap](https://github.com/deepfakes/faceswap) | Deepfakes Software For All | Python | 11 | 28863 | 30 | | :new: | 14 | [streamlit](https://github.com/streamlit/streamlit) | Streamlit — The fastest way to build custom ML tools | Python | 11 | 6650 | 31 | | :new: | 15 | [nni](https://github.com/microsoft/nni) | An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning. | Python | 11 | 5281 | 32 | | :new: | 16 | [yolov3](https://github.com/ultralytics/yolov3) | YOLOv3 in PyTorch > ONNX > CoreML > iOS | Jupyter Notebook | 10 | 3400 | 33 | | :new: | 17 | [book](https://github.com/KeKe-Li/book) | :books: All programming languages books | None | 10 | 4071 | 34 | | :arrow_up:28 | 18 | [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 | 10 | 10163 | 35 | | :arrow_up:13 | 19 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) | Jupyter Notebook | 9 | 36173 | 36 | | :arrow_up:11 | 20 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated JavaScript library for training and deploying ML models. | TypeScript | 9 | 12566 | 37 | | :new: | 21 | [carla](https://github.com/carla-simulator/carla) | Open-source simulator for autonomous driving research. | C++ | 9 | 3885 | 38 | | :arrow_down:2 | 22 | [Mask_RCNN](https://github.com/matterport/Mask_RCNN) | Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow | Python | 9 | 15583 | 39 | | :new: | 23 | [jetson-inference](https://github.com/dusty-nv/jetson-inference) | Guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson. | C++ | 9 | 2636 | 40 | | :arrow_up:35 | 24 | [awesome-deep-learning](https://github.com/ChristosChristofidis/awesome-deep-learning) | A curated list of awesome Deep Learning tutorials, projects and communities. | None | 8 | 14565 | 41 | | :new: | 25 | [catalyst](https://github.com/catalyst-team/catalyst) | Accelerated DL & RL | Python | 8 | 1544 | 42 | | :arrow_up:62 | 26 | [awesome-project-ideas](https://github.com/NirantK/awesome-project-ideas) | Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas | None | 8 | 3381 | 43 | | :arrow_down:2 | 27 | [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 | 8 | 15910 | 44 | | :arrow_down:12 | 28 | [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling) | Create HTML profiling reports from pandas DataFrame objects | Python | 8 | 4290 | 45 | | :arrow_down:17 | 29 | [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 | 8 | 22923 | 46 | | :new: | 30 | [spleeter](https://github.com/deezer/spleeter) | Deezer source separation library including pretrained models. | Python | 7 | 9752 | 47 | | :new: | 31 | [pytorch-lightning](https://github.com/PyTorchLightning/pytorch-lightning) | The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate | Python | 7 | 3512 | 48 | | :new: | 32 | [photoprism](https://github.com/photoprism/photoprism) | Personal Photo Management powered by Go and Google TensorFlow | Go | 7 | 4623 | 49 | | :arrow_down:22 | 33 | [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 | 7 | 18622 | 50 | | :new: | 34 | [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 | 7 | 25457 | 51 | | :heavy_minus_sign: | 35 | [deeplearning-models](https://github.com/rasbt/deeplearning-models) | A collection of various deep learning architectures, models, and tips | Jupyter Notebook | 7 | 11482 | 52 | | :new: | 36 | [trax](https://github.com/google/trax) | Trax — your path to advanced deep learning | Jupyter Notebook | 7 | 1649 | 53 | | :new: | 37 | [practicalAI](https://github.com/practicalAI/practicalAI) | 📚 A practical approach to machine learning. | Jupyter Notebook | 7 | 23437 | 54 | | :new: | 38 | [fashion-mnist](https://github.com/zalandoresearch/fashion-mnist) | A MNIST-like fashion product database. Benchmark :point_right: | Python | 6 | 7160 | 55 | | :arrow_up:61 | 39 | [mit-deep-learning](https://github.com/lexfridman/mit-deep-learning) | Tutorials, assignments, and competitions for MIT Deep Learning related courses. | Jupyter Notebook | 6 | 6899 | 56 | | :new: | 40 | [label-studio](https://github.com/heartexlabs/label-studio) | Label Studio is a multi-type data labeling and annotation tool with standardized output format | JavaScript | 6 | 2379 | 57 | | :new: | 41 | [ASRT_SpeechRecognition](https://github.com/nl8590687/ASRT_SpeechRecognition) | A Deep-Learning-Based Chinese Speech Recognition System 基于深度学习的中文语音识别系统 | Python | 6 | 2437 | 58 | | :new: | 42 | [nlp_overview](https://github.com/omarsar/nlp_overview) | Overview of Modern Deep Learning Techniques Applied to Natural Language Processing | CSS | 6 | 844 | 59 | | :arrow_up:8 | 43 | [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 | 6 | 23326 | 60 | | :new: | 44 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 6 | 15643 | 61 | | :arrow_up:42 | 45 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 6 | 9965 | 62 | | :arrow_up:33 | 46 | [stanford-cs-229-machine-learning](https://github.com/afshinea/stanford-cs-229-machine-learning) | VIP cheatsheets for Stanford's CS 229 Machine Learning | None | 6 | 9888 | 63 | | :arrow_up:7 | 47 | [dlaicourse](https://github.com/lmoroney/dlaicourse) | Notebooks for learning deep learning | Jupyter Notebook | 5 | 2184 | 64 | | :arrow_up:16 | 48 | [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 | 5 | 6350 | 65 | | :arrow_up:9 | 49 | [autokeras](https://github.com/keras-team/autokeras) | An AutoML system based on Keras | Python | 5 | 6561 | 66 | | :new: | 50 | [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 | 5 | 3910 | 67 | | :new: | 51 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 5 | 6450 | 68 | | :arrow_up:19 | 52 | [dgl](https://github.com/dmlc/dgl) | Python package built to ease deep learning on graph, on top of existing DL frameworks. | Python | 5 | 3944 | 69 | | :arrow_down:17 | 53 | [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 | 5 | 4348 | 70 | | :new: | 54 | [awesome-artificial-intelligence](https://github.com/owainlewis/awesome-artificial-intelligence) | A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers | None | 5 | 5239 | 71 | | :arrow_up:38 | 55 | [deep-learning-coursera](https://github.com/Kulbear/deep-learning-coursera) | Deep Learning Specialization by Andrew Ng on Coursera. | Jupyter Notebook | 5 | 4773 | 72 | | :arrow_up:30 | 56 | [nlp-tutorial](https://github.com/graykode/nlp-tutorial) | Natural Language Processing Tutorial for Deep Learning Researchers | Jupyter Notebook | 5 | 5176 | 73 | | :new: | 57 | [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 | 5 | 9350 | 74 | | :new: | 58 | [PySyft](https://github.com/OpenMined/PySyft) | A library for encrypted, privacy preserving machine learning | Python | 5 | 4819 | 75 | | :new: | 59 | [char-rnn](https://github.com/karpathy/char-rnn) | Multi-layer Recurrent Neural Networks (LSTM, GRU, RNN) for character-level language models in Torch | Lua | 5 | 9953 | 76 | | :arrow_up:21 | 60 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 5 | 27753 | 77 | | :arrow_down:51 | 61 | [fastai](https://github.com/fastai/fastai) | The fastai deep learning library, plus lessons and tutorials | Jupyter Notebook | 5 | 17001 | 78 | | :new: | 62 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 5 | 12951 | 79 | | :arrow_down:15 | 63 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 5 | 16203 | 80 | | :arrow_down:23 | 64 | [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++ | 5 | 15825 | 81 | | :new: | 65 | [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++ | 4 | 3914 | 82 | | :new: | 66 | [Dive-into-DL-TensorFlow2.0](https://github.com/TrickyGo/Dive-into-DL-TensorFlow2.0) | 本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的同意 | Jupyter Notebook | 4 | 1773 | 83 | | :new: | 67 | [Practical_RL](https://github.com/yandexdataschool/Practical_RL) | A course in reinforcement learning in the wild | Jupyter Notebook | 4 | 3716 | 84 | | :arrow_up:30 | 68 | [Awesome-PyTorch-Chinese](https://github.com/INTERMT/Awesome-PyTorch-Chinese) | 【干货】史上最全的PyTorch学习资源汇总 | Python | 4 | 1932 | 85 | | :new: | 69 | [ICCV2019-LearningToPaint](https://github.com/hzwer/ICCV2019-LearningToPaint) | ICCV2019 - A painting AI that can reproduce paintings stroke by stroke using deep reinforcement learning. | Python | 4 | 1583 | 86 | | :arrow_down:5 | 70 | [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 | 4 | 3790 | 87 | | :arrow_down:4 | 71 | [Stock-Prediction-Models](https://github.com/huseinzol05/Stock-Prediction-Models) | Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations | Jupyter Notebook | 4 | 1408 | 88 | | :new: | 72 | [deeplearning4j](https://github.com/eclipse/deeplearning4j) | Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning & linear algebra for Java/Scala with GPUs + Spark | Java | 4 | 11454 | 89 | | :arrow_down:16 | 73 | [bert-as-service](https://github.com/hanxiao/bert-as-service) | Mapping a variable-length sentence to a fixed-length vector using BERT model | Python | 4 | 6681 | 90 | | :new: | 74 | [Deep-learning-books](https://github.com/loveunk/Deep-learning-books) | Books for machine learning, deep learning, math, NLP, CV, RL, etc. 一些机器学习、深度学习等相关话题的书籍。 | None | 4 | 730 | 91 | | :arrow_down:1 | 75 | [labelImg](https://github.com/tzutalin/labelImg) | 🖍️ LabelImg is a graphical image annotation tool and label object bounding boxes in images | Python | 4 | 9635 | 92 | | :new: | 76 | [stanford-cs-230-deep-learning](https://github.com/afshinea/stanford-cs-230-deep-learning) | VIP cheatsheets for Stanford's CS 230 Deep Learning | None | 4 | 4017 | 93 | | :arrow_up:8 | 77 | [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 | 4 | 7534 | 94 | | :arrow_up:16 | 78 | [machine_learning_examples](https://github.com/lazyprogrammer/machine_learning_examples) | A collection of machine learning examples and tutorials. | Python | 4 | 4232 | 95 | | :new: | 79 | [albumentations](https://github.com/albumentations-team/albumentations) | fast image augmentation library and easy to use wrapper around other libraries | Python | 4 | 4336 | 96 | | :arrow_down:73 | 80 | [mediapipe](https://github.com/google/mediapipe) | MediaPipe is a cross-platform framework for building multimodal applied machine learning pipelines | C++ | 4 | 4458 | 97 | | :new: | 81 | [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 | 4 | 4463 | 98 | | :new: | 82 | [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 | 4 | 17947 | 99 | | :arrow_down:5 | 83 | [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 | 4 | 18344 | 100 | | :new: | 84 | [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 | 4 | 4703 | 101 | | :arrow_down:32 | 85 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 4 | 29775 | 102 | | :new: | 86 | [wav2letter](https://github.com/facebookresearch/wav2letter) | Facebook AI Research's Automatic Speech Recognition Toolkit | C++ | 4 | 4806 | 103 | | :new: | 87 | [seq2seq-couplet](https://github.com/wb14123/seq2seq-couplet) | Play couplet with seq2seq model. 用深度学习对对联。 | Python | 4 | 4060 | 104 | | :new: | 88 | [open_model_zoo](https://github.com/opencv/open_model_zoo) | Pre-trained Deep Learning models and samples (high quality and extremely fast) | Python | 4 | 1709 | 105 | | :new: | 89 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents Toolkit | Python | 4 | 7685 | 106 | | :arrow_down:10 | 90 | [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) | Deep Learning Examples | Jupyter Notebook | 4 | 3060 | 107 | | :new: | 91 | [deep-high-resolution-net.pytorch](https://github.com/leoxiaobin/deep-high-resolution-net.pytorch) | The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation" | Cuda | 4 | 2177 | 108 | | :new: | 92 | [awesome-mlss](https://github.com/sshkhr/awesome-mlss) | List of summer schools in machine learning + related fields across the globe | None | 4 | 621 | 109 | | :arrow_down:23 | 93 | [DeepLearning](https://github.com/Mikoto10032/DeepLearning) | 深度学习入门教程&&优秀文章&&Deep Learning Tutorial | Jupyter Notebook | 4 | 2308 | 110 | | :arrow_up:1 | 94 | [horovod](https://github.com/horovod/horovod) | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. | Python | 4 | 8517 | 111 | | :new: | 95 | [deep-learning-v2-pytorch](https://github.com/udacity/deep-learning-v2-pytorch) | Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101 | Jupyter Notebook | 4 | 2733 | 112 | | :new: | 96 | [cortex](https://github.com/cortexlabs/cortex) | Deploy machine learning models in production | Go | 4 | 2848 | 113 | | :new: | 97 | [pytorch-summary](https://github.com/sksq96/pytorch-summary) | Model summary in PyTorch similar to `model.summary()` in Keras | Python | 4 | 1952 | 114 | | :new: | 98 | [pwnagotchi](https://github.com/evilsocket/pwnagotchi) | (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning. | JavaScript | 4 | 3162 | 115 | | :new: | 99 | [cvat](https://github.com/opencv/cvat) | Powerful and efficient Computer Vision Annotation Tool (CVAT) | Python | 3 | 3074 | 116 | | :arrow_down:56 | 100 | [AI-Job-Notes](https://github.com/amusi/AI-Job-Notes) | 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） | None | 3 | 1857 | --------------------------------------------------------------------------------