{"id":21179548,"url":"https://github.com/mbadry1/trending-deep-learning","last_synced_at":"2025-04-05T01:05:39.696Z","repository":{"id":40201138,"uuid":"126902549","full_name":"mbadry1/Trending-Deep-Learning","owner":"mbadry1","description":"Top 100 trending deep learning repositories sorted by the number of stars gained on a specific day.","archived":false,"fork":false,"pushed_at":"2020-02-02T11:57:07.000Z","size":94,"stargazers_count":643,"open_issues_count":1,"forks_count":218,"subscribers_count":63,"default_branch":"master","last_synced_at":"2025-03-29T00:06:18.537Z","etag":null,"topics":["artificial-intelligence","artificial-neural-networks","convolutional-neural-networks","deep-learning","deep-neural-networks","deep-reinforcement-learning","machine-learning","recurrent-neural-networks","stargazers-count","trending-repositories"],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mbadry1.png","metadata":{"files":{"readme":"readme.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-03-26T23:39:30.000Z","updated_at":"2025-03-19T14:36:26.000Z","dependencies_parsed_at":"2022-08-29T14:31:27.937Z","dependency_job_id":null,"html_url":"https://github.com/mbadry1/Trending-Deep-Learning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mbadry1%2FTrending-Deep-Learning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mbadry1%2FTrending-Deep-Learning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mbadry1%2FTrending-Deep-Learning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mbadry1%2FTrending-Deep-Learning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mbadry1","download_url":"https://codeload.github.com/mbadry1/Trending-Deep-Learning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247271525,"owners_count":20911587,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["artificial-intelligence","artificial-neural-networks","convolutional-neural-networks","deep-learning","deep-neural-networks","deep-reinforcement-learning","machine-learning","recurrent-neural-networks","stargazers-count","trending-repositories"],"created_at":"2024-11-20T17:32:00.822Z","updated_at":"2025-04-05T01:05:39.671Z","avatar_url":"https://github.com/mbadry1.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Trending deep learning Github repositories\n\nHere'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:\n\n- `deep-learning OR CNN OR RNN OR \"convolutional neural network\" OR \"recurrent neural network\"`\n\nRepositories with 40000 stars or more are excluded.\n\nTop deep learning Github repositories can be found [here](https://github.com/mbadry1/Top-Deep-Learning).\n\nDate: 02-02-2020 compared to 09-01-2019\n\nNote: This will be updated regularly.\n\n| | Pos1 | Name | Description | Language | Stars Today | Total Stars |\n|--------------------|------|---------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|-------------|-------------|\n| :new: | 1 | [spinningup](https://github.com/openai/spinningup) | An educational resource to help anyone learn deep reinforcement learning. | Python | 53 | 4030 |\n| :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 |\n| :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 |\n| :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 |\n| :arrow_up:1 | 5 | [DeepFaceLab](https://github.com/iperov/DeepFaceLab) | DeepFaceLab is the leading software for creating deep fakes. | Python | 15 | 12237 |\n| :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 |\n| :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 |\n| :new: | 8 | [thinc](https://github.com/explosion/thinc) | 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries | Python | 15 | 1683 |\n| :arrow_up:15 | 9 | [pytorch-tutorial](https://github.com/yunjey/pytorch-tutorial) | PyTorch Tutorial for Deep Learning Researchers | Python | 14 | 15314 |\n| :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 |\n| :arrow_up:3 | 11 | [pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration | C++ | 14 | 35719 |\n| :arrow_up:35 | 12 | [pytorch_geometric](https://github.com/rusty1s/pytorch_geometric) | Geometric Deep Learning Extension Library for PyTorch | Python | 11 | 6473 |\n| :arrow_down:11 | 13 | [faceswap](https://github.com/deepfakes/faceswap) | Deepfakes Software For All | Python | 11 | 28863 |\n| :new: | 14 | [streamlit](https://github.com/streamlit/streamlit) | Streamlit — The fastest way to build custom ML tools | Python | 11 | 6650 |\n| :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 |\n| :new: | 16 | [yolov3](https://github.com/ultralytics/yolov3) | YOLOv3 in PyTorch \u003e ONNX \u003e CoreML \u003e iOS | Jupyter Notebook | 10 | 3400 |\n| :new: | 17 | [book](https://github.com/KeKe-Li/book) | :books: All programming languages books | None | 10 | 4071 |\n| :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 |\n| :arrow_up:13 | 19 | [TensorFlow-Examples](https://github.com/aymericdamien/TensorFlow-Examples) | TensorFlow Tutorial and Examples for Beginners (support TF v1 \u0026 v2) | Jupyter Notebook | 9 | 36173 |\n| :arrow_up:11 | 20 | [tfjs](https://github.com/tensorflow/tfjs) | A WebGL accelerated JavaScript library for training and deploying ML models. | TypeScript | 9 | 12566 |\n| :new: | 21 | [carla](https://github.com/carla-simulator/carla) | Open-source simulator for autonomous driving research. | C++ | 9 | 3885 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 25 | [catalyst](https://github.com/catalyst-team/catalyst) | Accelerated DL \u0026 RL | Python | 8 | 1544 |\n| :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 |\n| :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 |\n| :arrow_down:12 | 28 | [pandas-profiling](https://github.com/pandas-profiling/pandas-profiling) | Create HTML profiling reports from pandas DataFrame objects | Python | 8 | 4290 |\n| :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 |\n| :new: | 30 | [spleeter](https://github.com/deezer/spleeter) | Deezer source separation library including pretrained models. | Python | 7 | 9752 |\n| :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 |\n| :new: | 32 | [photoprism](https://github.com/photoprism/photoprism) | Personal Photo Management powered by Go and Google TensorFlow | Go | 7 | 4623 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 36 | [trax](https://github.com/google/trax) | Trax — your path to advanced deep learning | Jupyter Notebook | 7 | 1649 |\n| :new: | 37 | [practicalAI](https://github.com/practicalAI/practicalAI) | 📚 A practical approach to machine learning. | Jupyter Notebook | 7 | 23437 |\n| :new: | 38 | [fashion-mnist](https://github.com/zalandoresearch/fashion-mnist) | A MNIST-like fashion product database. Benchmark :point_right: | Python | 6 | 7160 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 42 | [nlp_overview](https://github.com/omarsar/nlp_overview) | Overview of Modern Deep Learning Techniques Applied to Natural Language Processing | CSS | 6 | 844 |\n| :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 |\n| :new: | 44 | [spaCy](https://github.com/explosion/spaCy) | 💫 Industrial-strength Natural Language Processing (NLP) with Python and Cython | Python | 6 | 15643 |\n| :arrow_up:42 | 45 | [facenet](https://github.com/davidsandberg/facenet) | Face recognition using Tensorflow | Python | 6 | 9965 |\n| :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 |\n| :arrow_up:7 | 47 | [dlaicourse](https://github.com/lmoroney/dlaicourse) | Notebooks for learning deep learning | Jupyter Notebook | 5 | 2184 |\n| :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 |\n| :arrow_up:9 | 49 | [autokeras](https://github.com/keras-team/autokeras) | An AutoML system based on Keras | Python | 5 | 6561 |\n| :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 |\n| :new: | 51 | [Keras-GAN](https://github.com/eriklindernoren/Keras-GAN) | Keras implementations of Generative Adversarial Networks. | Python | 5 | 6450 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :arrow_up:30 | 56 | [nlp-tutorial](https://github.com/graykode/nlp-tutorial) | Natural Language Processing Tutorial for Deep Learning Researchers | Jupyter Notebook | 5 | 5176 |\n| :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 |\n| :new: | 58 | [PySyft](https://github.com/OpenMined/PySyft) | A library for encrypted, privacy preserving machine learning | Python | 5 | 4819 |\n| :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 |\n| :arrow_up:21 | 60 | [deeplearningbook-chinese](https://github.com/exacity/deeplearningbook-chinese) | Deep Learning Book Chinese Translation | TeX | 5 | 27753 |\n| :arrow_down:51 | 61 | [fastai](https://github.com/fastai/fastai) | The fastai deep learning library, plus lessons and tutorials | Jupyter Notebook | 5 | 17001 |\n| :new: | 62 | [DeepSpeech](https://github.com/mozilla/DeepSpeech) | A TensorFlow implementation of Baidu's DeepSpeech architecture | C++ | 5 | 12951 |\n| :arrow_down:15 | 63 | [darknet](https://github.com/pjreddie/darknet) | Convolutional Neural Networks | C | 5 | 16203 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 67 | [Practical_RL](https://github.com/yandexdataschool/Practical_RL) | A course in reinforcement learning in the wild | Jupyter Notebook | 4 | 3716 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 72 | [deeplearning4j](https://github.com/eclipse/deeplearning4j) | Eclipse Deeplearning4j, ND4J, DataVec and more - deep learning \u0026 linear algebra for Java/Scala with GPUs + Spark | Java | 4 | 11454 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :new: | 79 | [albumentations](https://github.com/albumentations-team/albumentations) | fast image augmentation library and easy to use wrapper around other libraries | Python | 4 | 4336 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :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 |\n| :arrow_down:32 | 85 | [caffe](https://github.com/BVLC/caffe) | Caffe: a fast open framework for deep learning. | C++ | 4 | 29775 |\n| :new: | 86 | [wav2letter](https://github.com/facebookresearch/wav2letter) | Facebook AI Research's Automatic Speech Recognition Toolkit | C++ | 4 | 4806 |\n| :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 |\n| :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 |\n| :new: | 89 | [ml-agents](https://github.com/Unity-Technologies/ml-agents) | Unity Machine Learning Agents Toolkit | Python | 4 | 7685 |\n| :arrow_down:10 | 90 | [DeepLearningExamples](https://github.com/NVIDIA/DeepLearningExamples) | Deep Learning Examples | Jupyter Notebook | 4 | 3060 |\n| :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 |\n| :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 |\n| :arrow_down:23 | 93 | [DeepLearning](https://github.com/Mikoto10032/DeepLearning) | 深度学习入门教程\u0026\u0026优秀文章\u0026\u0026Deep Learning Tutorial | Jupyter Notebook | 4 | 2308 |\n| :arrow_up:1 | 94 | [horovod](https://github.com/horovod/horovod) | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. | Python | 4 | 8517 |\n| :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 |\n| :new: | 96 | [cortex](https://github.com/cortexlabs/cortex) | Deploy machine learning models in production | Go | 4 | 2848 |\n| :new: | 97 | [pytorch-summary](https://github.com/sksq96/pytorch-summary) | Model summary in PyTorch similar to `model.summary()` in Keras | Python | 4 | 1952 |\n| :new: | 98 | [pwnagotchi](https://github.com/evilsocket/pwnagotchi) | (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning. | JavaScript | 4 | 3162 |\n| :new: | 99 | [cvat](https://github.com/opencv/cvat) | Powerful and efficient Computer Vision Annotation Tool (CVAT) | Python | 3 | 3074 |\n| :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 |","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmbadry1%2Ftrending-deep-learning","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmbadry1%2Ftrending-deep-learning","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmbadry1%2Ftrending-deep-learning/lists"}