Topics / #neural-networks

Neural-networks projects on GitHub

Plural variant of the neural network topic: architectures and training.

As of , the most-starred Neural-networks projects on GitHub are annotated_deep_learning_paper_implementations (67.6K stars), keras (64.4K stars) and faceswap (57.6K stars). GitHub.Locker tracks 57 Neural-networks repositories with 1.2M stars combined. The fastest-growing on October 16 was video2x, with +18 stars in a day.

57Projects
1.2MStars in total
+173Stars in a day
Browse in the catalog →github.com/topics/neural-networks ↗

Hot right now

Most stars gained in a day · Oct 16

+18

video2x

k4yt3x/video2x · ★ 22.3K

Video2X is an open-source video super resolution and frame interpolation tool: it uses machine learning to upscale low-resolution videos to higher quality and to add interpolated frames for smoother motion.

+13

onnxruntime

microsoft/onnxruntime · ★ 22.1K

ONNX Runtime is a cross-platform, high performance ML accelerator for inference and training. It runs models from PyTorch, TensorFlow/Keras and classical ML libraries like scikit-learn, LightGBM and XGBoost.

+10

d2l-en

d2l-ai/d2l-en · ★ 29.9K

An interactive open-source deep learning book that teaches concepts, context, and runnable code together, with examples in multiple frameworks. Its premise: the best way to understand deep learning is learning by doing.

+10

nn-zero-to-hero

karpathy/nn-zero-to-hero · ★ 24.8K

A course by Andrej Karpathy that teaches neural networks from the absolute basics, built around a series of YouTube lectures with accompanying Jupyter notebooks coded live in the videos.

The all-time top

57 projects · by stars

  1. #1 · labmlai/annotated_deep_learning_paper_implementations

    annotated_deep_learning_paper_implementations

    A collection of 60+ PyTorch implementations of deep learning papers, each annotated with side-by-side explanatory notes so you can read the code and the math/explanation together.

    67.6K
  2. #2 · keras-team/keras

    keras

    Keras 3 is a multi-backend deep learning framework that lets you build and train models for computer vision, NLP, audio, timeseries, and recommender systems on top of JAX, TensorFlow, or PyTorch.

    64.4K
  3. #3 · deepfakes/faceswap

    faceswap

    FaceSwap is a Python tool that uses deep learning to recognize and swap faces in pictures and videos.

    57.6K
  1. 4

    ailearning

    42.6Kapachecn/ailearning · Python

    AiLearning is a Chinese-language, practice-first study guide covering data analysis, machine learning, linear algebra, PyTorch, NLTK, and TensorFlow 2, built mainly around code-along notes for the book 'Machine Learning in Action'.

  2. 5

    bert

    40Kgoogle-research/bert · Python

    Google's official TensorFlow implementation of BERT together with pre-trained checkpoints — a method for pre-training language representations that set state-of-the-art results on a wide range of NLP tasks, from SQuAD question answering to natural language inference.

  3. 6

    Coursera-ML-AndrewNg-Notes

    38Kfengdu78/Coursera-ML-AndrewNg-Notes · HTML

    This is Huang Haiguang's personal Chinese-language notes on Andrew Ng's 2014 Stanford/Coursera Machine Learning course, covering every lecture, the slides, and exercise code.

  4. 7

    LLM101n

    37.5Kkarpathy/LLM101n

    LLM101n is a planned course by Andrej Karpathy that walks through building a 'Storyteller' AI language model end-to-end, from basics all the way to a ChatGPT-like web app, implemented from scratch in Python, C and CUDA.

  5. 8

    ControlNet

    34.1Klllyasviel/ControlNet · Python

    ControlNet is a neural network structure that adds extra conditions to diffusion models like Stable Diffusion: instead of a text prompt alone, you steer generation with an edge map, depth map, pose skeleton or scribble. This repo is the official implementation.

  6. 9

    spaCy

    34Kexplosion/spaCy · Python

    spaCy is a library for advanced Natural Language Processing in Python and Cython, designed from day one for real products. It ships pretrained pipelines and supports tokenization and training for 70+ languages.

  7. 10

    ML-From-Scratch

    33Keriklindernoren/ML-From-Scratch · Python

    A Python library of fundamental machine learning models and algorithms implemented from scratch in NumPy, aiming to cover everything from linear regression to deep learning.

  8. 11

    pytorch-tutorial

    32.5Kyunjey/pytorch-tutorial · Python

    This is a collection of PyTorch tutorial code for deep learning researchers, covering models from basics to advanced topics, each implemented in under 30 lines of code where possible.

  9. 12

    tuning_playbook

    30.4Kgoogle-research/tuning_playbook

    A free, in-depth guide from five Google Research Brain Team researchers (plus a Harvard co-author) on systematically maximizing the performance of deep learning models — the 'Deep Learning Tuning Playbook'.

  10. 13

    d2l-en

    29.9Kd2l-ai/d2l-en · Python

    An interactive open-source deep learning book that teaches concepts, context, and runnable code together, with examples in multiple frameworks. Its premise: the best way to understand deep learning is learning by doing.

  11. 14

    awesome-deep-learning

    29.1KChristosChristofidis/awesome-deep-learning

    A curated GitHub list of deep learning tutorials, projects and communities, with about 29,000 stars. It's a jumping-off point for learning the field, not software you run.

  12. 15

    DeepSpeech

    26.8Kmozilla/DeepSpeech · C++

    Mozilla DeepSpeech is an open-source Speech-To-Text engine — a machine-learning model that turns audio into text on your own hardware.

  13. 16

    deep-learning-for-image-processing

    26.4KWZMIAOMIAO/deep-learning-for-image-processing · Python

    A video-based deep learning course that walks through classic computer-vision architectures for image classification, object detection, segmentation and keypoint detection, pairing each network with a lecture and runnable code.

  14. 17

    nn-zero-to-hero

    24.8Kkarpathy/nn-zero-to-hero · Jupyter Notebook

    A course by Andrej Karpathy that teaches neural networks from the absolute basics, built around a series of YouTube lectures with accompanying Jupyter notebooks coded live in the videos.

  15. 18

    Paddle

    24.1KPaddlePaddle/Paddle · C++

    PaddlePaddle is an open-source deep learning platform — China's first independently developed one, open-sourced since 2016 — spanning a core framework, model libraries, end-to-end dev kits and service platforms.

  16. 19

    pytorch_geometric

    24.1Kpyg-team/pytorch_geometric · Python

    PyG (PyTorch Geometric) is a Python library built on PyTorch for writing and training Graph Neural Networks (GNNs) on structured data — graphs and other irregular structures — using methods drawn from many published papers.

  17. 20

    video2x

    22.3Kk4yt3x/video2x · C++

    Video2X is an open-source video super resolution and frame interpolation tool: it uses machine learning to upscale low-resolution videos to higher quality and to add interpolated frames for smoother motion.

  18. 21

    100-Days-Of-ML-Code

    22.2KMLEveryday/100-Days-Of-ML-Code · Python

    The Chinese edition of the 100 Days of ML Code challenge: a day-by-day machine learning learning log with infographics, notes and Python code, spanning supervised and unsupervised learning. It translates the original challenge by Avik-Jain and has gathered 22k+ stars.

  19. 22

    onnxruntime

    22.1Kmicrosoft/onnxruntime · C++

    ONNX Runtime is a cross-platform, high performance ML accelerator for inference and training. It runs models from PyTorch, TensorFlow/Keras and classical ML libraries like scikit-learn, LightGBM and XGBoost.

  20. 23

    Anime4K

    21.5Kbloc97/Anime4K · Jupyter Notebook

    Anime4K is a set of open-source, real-time upscaling and denoising algorithms, implemented as GLSL shaders, that sharpen and upscale anime video on the fly inside your media player instead of permanently re-encoding the file.

  21. 24

    deeplearning_ai_books

    21.2Kfengdu78/deeplearning_ai_books · HTML

    A Chinese-language collection of notes covering Andrew Ng's (吴恩达) Deep Learning Specialization on Coursera — five courses on neural networks, hyperparameter tuning, structuring ML projects, CNNs, and sequence models.

  22. 25

    stanford-cs-229-machine-learning

    20.3Kafshinea/stanford-cs-229-machine-learning

    A collection of cheatsheets and refreshers that summarize all the key concepts taught in Stanford's CS 229 Machine Learning course, covering supervised learning, unsupervised learning, deep learning, and training tips.

  23. 26

    ml-agents

    19.8KUnity-Technologies/ml-agents · C#

    Unity ML-Agents Toolkit lets Unity games and simulations act as training environments for AI agents, using deep reinforcement learning and imitation learning. It pairs a Unity SDK with a Python API so game developers and researchers can train NPCs, test builds, or evaluate design decisions.

  24. 27

    Dive-into-DL-PyTorch

    19.5KShusenTang/Dive-into-DL-PyTorch · Jupyter Notebook

    The Chinese book 'Dive into Deep Learning' with its MXNet code examples rewritten in PyTorch — a free, open-source deep-learning tutorial pairing runnable Jupyter notebooks with online docs.

  25. 28

    nndl

    19.4Knndl/nndl

    The official home of Qiu Xipeng's Chinese textbook 'Neural Network and Deep Learning': it hosts free e-book PDFs, chapter listings, learning resources and errata for the 2nd edition and the new general-audience edition.

  26. 29

    DeepFaceLab

    19.3Kiperov/DeepFaceLab · Python

    DeepFaceLab is a deep-learning toolkit for creating deepfakes - it lets you replace a face, de-age a face, or even replace an entire head in video footage.

  27. 30

    Speech

    18.6KNVIDIA-NeMo/Speech · Python

    An open-source NVIDIA framework for building speech AI models — automatic speech recognition (ASR), text-to-speech (TTS), and speech LLMs — with pre-trained checkpoints you can customize and deploy.

  28. 31

    Machine-Learning-Tutorials

    18.3Kujjwalkarn/Machine-Learning-Tutorials

    A topic-wise curated list of machine learning and deep learning tutorials, articles and other resources, maintained as a single GitHub README.

  29. 32

    neural-networks-and-deep-learning

    18Kmnielsen/neural-networks-and-deep-learning · Python

    Code samples for Michael Nielsen's book 'Neural Networks and Deep Learning' — a set of Python programs meant to be read and run while working through the book.

  30. 33

    vision

    18Kpytorch/vision · Python

    Torchvision is PyTorch's computer vision package: popular datasets, ready-made model architectures, and common image transformations for vision work.

  31. 34

    CNTK

    17.6Kmicrosoft/CNTK · C++

    The Microsoft Cognitive Toolkit (CNTK) is an open-source deep-learning toolkit that describes neural networks as a series of computational steps in a directed graph.

  32. 35

    numpy-ml

    16.3Kddbourgin/numpy-ml · Python

    A collection of machine learning algorithms — Gaussian mixture models, HMMs, neural networks, tree ensembles, reinforcement learning agents and more — implemented from scratch in pure NumPy.

  33. 36

    lectures

    15.9Koxford-cs-deepnlp-2017/lectures

    The lecture slides and course description for the Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford: an advanced, applied NLP course organised by Phil Blunsom and delivered in partnership with the DeepMind Natural Language Research Group.

  34. 37

    deepmind-research

    15.2Kgoogle-deepmind/deepmind-research · Jupyter Notebook

    It is Google DeepMind's research repository: implementations and illustrative code that accompany its published papers, released alongside open-source environments and datasets the community can build on.

  35. 38

    nlp-tutorial

    14.9Kgraykode/nlp-tutorial · Jupyter Notebook

    A collection of short PyTorch implementations covering core NLP and deep learning models, from word embeddings to Transformers and BERT, meant as a study resource.

  36. 39

    stylegan

    14.4KNVlabs/stylegan · Python

    NVIDIA's official TensorFlow implementation of StyleGAN, a generative adversarial network that synthesizes photorealistic images — most famously 1024x1024 faces of people who don't exist — with intuitive control over attributes like pose and identity.

  37. 40

    deeplearning4j

    14.3Kdeeplearning4j/deeplearning4j · Java

    Eclipse Deeplearning4J is a suite of JVM libraries for building, training and deploying deep learning applications, usable from Java, Scala, Kotlin and Clojure.

  38. 41

    mit-deep-learning-book-pdf

    14.3Kjanishar/mit-deep-learning-book-pdf · Java

    This repo provides PDF versions (chapter-wise and complete) of the MIT Press book 'Deep Learning' by Ian Goodfellow, Yoshua Bengio and Aaron Courville, which is otherwise only available as an HTML book online.

  39. 42

    Deep-Learning-with-TensorFlow-book

    13.2Kdragen1860/Deep-Learning-with-TensorFlow-book · Jupyter Notebook

    A free, open-source Chinese textbook on deep learning built on the official TensorFlow 2 release, pairing theory with hands-on case studies. This repo ships the PDF e-book, the accompanying source code, and the lecture slides.

  40. 43

    char-rnn

    12.1Kkarpathy/char-rnn · Lua

    A multi-layer Recurrent Neural Network implementation (vanilla RNN, LSTM, GRU) in Torch/Lua for training and sampling character-level language models that learn to predict the next character in a text and can then generate new text that mimics it.

  41. 44

    Pytorch-UNet

    11.7Kmilesial/Pytorch-UNet · Python

    A PyTorch implementation of the U-Net convolutional network for semantic segmentation, customized for Kaggle's Carvana Image Masking Challenge on high-definition images.

  42. 45

    ganhacks

    11.6Ksoumith/ganhacks

    A short cheat sheet of practical tips and tricks for training Generative Adversarial Networks (GANs), originally put together as a handout from the 'How to Train a GAN?' session at NIPS 2016.

  43. 46

    MLAlgorithms

    11.2Krushter/MLAlgorithms · Python

    A collection of minimal, clean Python implementations of core machine learning algorithms, built so people can learn how the algorithms actually work internally.

  44. 47

    fast-style-transfer

    11Klengstrom/fast-style-transfer · Python

    This is a TensorFlow implementation of fast neural style transfer: once trained, it applies the artistic style of a painting to a photo or video in a fraction of a second, building on the Gatys, Johnson, and Ulyanov style-transfer papers.

  45. 48

    pix2pix

    10.7Kphillipi/pix2pix · Lua

    This is the original Torch/Lua implementation accompanying the pix2pix paper (CVPR 2017), which learns to translate images from one style into another — e.g. label maps to photos, or sketches to shoes — using a conditional GAN.

  46. 49

    petals

    10.6Kbigscience-workshop/petals · Python

    Petals lets you run big open LLMs at home, BitTorrent-style: you join a public swarm that serves models like Llama 3.1 (405B), Mixtral (8x22B), Falcon (40B+) and BLOOM (176B) for inference and fine-tuning right from your desktop or Google Colab, up to 10x faster than offloading.

  47. 50

    yolov3

    10.6Kultralytics/yolov3 · Python

    Ultralytics' PyTorch implementation of the YOLOv3 real-time object detector, packaging three model variants - YOLOv3, YOLOv3-SPP and YOLOv3-tiny - with training, validation, inference and multi-format export tooling.

  48. 51

    mit-deep-learning

    10.5Klexfridman/mit-deep-learning · Jupyter Notebook

    This repository collects tutorials, assignments, and competitions from MIT's Deep Learning related courses, covering semantic segmentation, generative adversarial networks, and reinforcement learning for self-driving cars.

  49. 52

    lama

    10.3Kadvimman/lama · Jupyter Notebook

    LaMa is an AI image inpainting model with its research code: it removes unwanted objects and fills in large missing regions of photos using Fourier convolutions, staying reliable even at high resolutions. It is the official code of a WACV 2022 paper.

  50. 53

    3D-Machine-Learning

    10.2Ktimzhang642/3D-Machine-Learning

    A curated knowledge base for 3D machine learning that collects courses, datasets, and research papers covering 3D representations like point clouds, meshes, voxels and primitives.

  51. 54

    data-science-interviews

    10.2Kalexeygrigorev/data-science-interviews · HTML

    A free, community-built collection of data science interview questions with answers, stored as markdown files in this repo.

  52. 55

    bdh

    3.6Kpathwaycom/bdh · Python

    BDH (Dragon Hatchling) is a biologically inspired large language model architecture that connects deep learning with neuroscience, aiming to explain how reasoning and generalization emerge in AI systems at the level of individual neuron interactions.

  53. 56

    dqn-adaptive-cpu-scheduler

    1.5Kaaawangyh/dqn-adaptive-cpu-scheduler · Python

    This is a research-grade repository that implements an adaptive CPU task scheduler trained with a Deep Q-Network (DQN). It includes a simulator of multi-core CPUs with DVFS and a thermal-aware reward, plus training, evaluation, and plotting pipelines.

  54. 57

    cadence

    449muellerberndt/cadence · Python

    Cadence is an open research library toward general intelligence: a NumPy collection of 'brains' that compute by settling into an equilibrium and learn by detuning it, aiming to acquire skills from live experience the way animals and humans do.

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