Python neural-networks

Open-source Python projects categorized as neural-networks | Edit details

Top 23 Python neural-network Projects

  • GitHub repo Keras

    Deep Learning for humans

    Project mention: That time I optimized a Python program by 5000x | | 2022-01-11

    The report output for scalene does look much nicer, but the slowness for me dropped me from continuing to use it. Maybe there's some bad interaction with tensorflow/pytest. I can try to make an example, but I'd guess if you try running it on tensorflows actual unit tests (something like this) you'd get similar behavior.

  • GitHub repo faceswap

    Deepfakes Software For All

    Project mention: Use the infamous Deep Fakes project for things other than faces | | 2021-10-25

    My current challenge is getting those masked wheel images to be able to swap between images, or to apply a new wheel on a car image. To get a decent result that doesn't look fake, it would have to do some minor warping and resizing. To me, this seems like exactly what the Deep Fakes repo does.

  • Scout APM

    Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.

  • GitHub repo DeepFaceLab

    DeepFaceLab is the leading software for creating deepfakes.

    Project mention: Top Github repo trends in 2021 | | 2022-01-12

    AI/ML is awesome and will bring a ton of good to the world, but there are also serious risks and safety considerations. Enhanced surveillance and State control is certainly one of them, and perhaps one of the ripest use cases for abuse is around facial recognition. One of the top trending repos in 2021 was Tencent’s GFPGAN, which ‘aims at developing Practical Algorithms for Real-world Face Restoration’. Another trending library was DeepFaceLab, for creating deep fakes. Note, famously in 2020, Huawei published about testing software for facial recognition of Uighurs. Earlier that year, IBM announced it would no longer develop facial recognition software. I come from a country where state surveillance is fairly normalized, albeit discreet. I’m talking journalists have their homes broken into, their messenger texts intercepted, and the secret police taps your cell phone type surveillance. So when our government bought 1000+ Huawei smart cameras a couple years back with facial recognition embedded, human rights activist were not thrilled.

  • GitHub repo pytorch-tutorial

    PyTorch Tutorial for Deep Learning Researchers

    Project mention: How to 'practice' pytorch after finishing its basic tutorial? | | 2021-05-09

    I tried to move straight to practicing implementing papers and trying to understand other people's codes but failed miserably. I feel like there was too much of a gap between the basic tutorial and being able to implement ideas into code....hence the question: Is there any resource/way to practice pytorch in general? I did find this and this, but I just wanted to hear what others have gone through to become better at PyTorch up to the point they can build stuff from their own ideas

  • GitHub repo spaCy

    💫 Industrial-strength Natural Language Processing (NLP) in Python

    Project mention: Topic modelling with Gensim and SpaCy on startup news | | 2022-01-17

    SpaCy is one of the most popular NLP libraries, and is very fast and flexible.

  • GitHub repo fast-style-transfer

    TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

    Project mention: Where to learn how to turn photos into images in the style of famous painters? | | 2021-10-25

    Try: . There are links to the underlying papers.

  • GitHub repo pyod

    (JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

    Project mention: [D] Unsupervised Outlier Detection - Advise Requested | | 2021-12-03

    The source code and documentaion of PyOD is the best survey about OOD. Besides, the normalized flow and VQVAE are also feasible.

  • OPS

    OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.

  • GitHub repo segmentation_models.pytorch

    Segmentation models with pretrained backbones. PyTorch.

    Project mention: Advice needed | | 2021-10-02

    You could also use qubvel's segmentation models if you would like to explore semantic segmentation.

  • GitHub repo igel

    a delightful machine learning tool that allows you to train, test, and use models without writing code

    Project mention: Train/fit, test, and use models without writing code | | 2021-06-29

    Link to the repo:

  • GitHub repo hummingbird

    Hummingbird compiles trained ML models into tensor computation for faster inference.

    Project mention: Export and run models with ONNX | | 2021-09-07

    ONNX opens an avenue for direct inference using a number of languages and platforms. For example, a model could be run directly on Android to limit data sent to a third party service. ONNX is an exciting development with a lot of promise. Microsoft has also released Hummingbird which enables exporting traditional models (sklearn, decision trees, logistical regression..) to ONNX.

  • GitHub repo dm_control

    DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

    Project mention: [D] MuJoCo vs PyBullet? (esp. for custom environment) | | 2021-12-07

    If you're interested in using Mujoco, I'd suggest checking out the dm_control package for Python bindings rather than interfacing with C++ directly. I think one downside to Mujoco currently is that you cannot dynamically add objects, and the entire simulation is initialized and loaded according to the MJCF / XML file.

  • GitHub repo BigGAN-PyTorch

    The author's officially unofficial PyTorch BigGAN implementation.

    Project mention: [D] Using activity regularization instead of batch norm. | | 2021-04-03

    Tangentially, theoretically you can't use BN in the discriminator for WGAN-GP anyway (assuming that you're using the Gulrajani work) because it breaks the sample independence assumptions of the GP. If you have a relatively structured dataset (eg all faces, all cars, all giraffes, etc.) and no class conditioning, look into StyleGAN2-ADA for the best results. If you have a dataset with a lot of variation and a lot of classes try using the BigGAN repo.

  • GitHub repo GAT

    Graph Attention Networks (

    Project mention: Graph Attention Networks (GAT) v2 implementation with side-by-side notes | | 2021-08-06

    Code for found:

  • GitHub repo NCRFpp

    NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

    Project mention: Speech and Language Processing (3rd ed. draft) | | 2021-10-17

    They still talk about Hidden Markov Models (HMMs) in quite a bit of detail in the sequence labelling chapter, but you are quite right, Conditional Random Fields (CRFs) and especially neural network based CRFs are in the top rankings when it comes to named entity recognition (NER) and part-of-speech tagging (POS), e.g. see

  • GitHub repo pytorch-forecasting

    Time series forecasting with PyTorch

    Project mention: When to go for an 'easy' time-series model vs. using a complex deep learning model (when having experience with the latter) | | 2021-11-29

    I'm a data trainee at this organisation. I wrote my master thesis about using an event clustering mechanism to enrich an existing dataset to improve short-term demand predictions, using Pytorch Forecasting using the temporal fusion transformer component, and LightGBM (and compare the models with and w/o the event feature, so 4 runs in total).

  • GitHub repo dm-haiku

    JAX-based neural network library

    Project mention: PyTorch vs. TensorFlow in 2022 | | 2021-12-14

    As a researcher in RL & ML in a big industry lab, I would say most of my colleagues are moving to JAX 0], which this article kind of ignores. JAX is XLA-accelerated NumPy, it's cool beyond just machine learning, but only provides low-level linear algebra abstractions. However you can put something like Haiku [] or Flax [] on top of it and get what the cool kids are using :)

  • GitHub repo transfer-learning-conv-ai

    🦄 State-of-the-Art Conversational AI with Transfer Learning

    Project mention: Messing around with an AI | | 2021-03-20 (Requires an hefty GPU though...)

  • GitHub repo minisom

    :red_circle: MiniSom is a minimalistic implementation of the Self Organizing Maps

    Project mention: [P][D] Self Organizing Maps | | 2021-07-15
  • GitHub repo hivemind

    Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.

    Project mention: GPT-3 Is No Longer the Only Game in Town | | 2021-11-07

    The problem is that, currently, large ML models need to be trained on clusters of tightly-connected GPUs/accelerators. So it's kinda useless having a bunch of GPUs spread all over the world with huge latency and low bandwidth between them. That may change though - there are people working on it:

  • GitHub repo deepxde

    A library for scientific machine learning

    Project mention: Physics-Informed ML Simulator for Wildfire Propagation (Video) | | 2021-02-15
  • GitHub repo deep_learning_and_the_game_of_go

    Code and other material for the book "Deep Learning and the Game of Go"

    Project mention: Why do engines often evaluate completely winning endgame positions between +60 and +63? What's significant about the low 60's as an evaluation? Or is it just a placeholder when the computer can't quite find a forced mate? | | 2021-12-06

    If you want to understand how the new approach used by Leela Zero and Alpha Zero works, the book Deep Learning and the Game of Go is fun and easy to read. Although it's about Go rather than chess, most of the contents are equally relevant to chess.

  • GitHub repo uncertainty-baselines

    High-quality implementations of standard and SOTA methods on a variety of tasks.

    Project mention: Google AI Introduces ‘Uncertainty Baselines Library’ For Uncertainty and Robustness in Deep Learning | | 2021-10-17

    Code for found:

  • GitHub repo GeneticAlgorithmPython

    Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

    Project mention: [D] Shape Generation Algorithm | | 2021-12-03

    My pleasure! I'm assuming you're working in Python, so this repo looks like it could be promising (disclaimer: I haven't used it).

NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020). The latest post mention was on 2022-01-17.

Python neural-networks related posts


What are some of the best open-source neural-network projects in Python? This list will help you:

Project Stars
1 Keras 53,748
2 faceswap 40,151
3 DeepFaceLab 30,841
4 pytorch-tutorial 22,814
5 spaCy 22,176
6 fast-style-transfer 10,277
7 pyod 5,181
8 segmentation_models.pytorch 4,752
9 igel 2,963
10 hummingbird 2,723
11 dm_control 2,637
12 BigGAN-PyTorch 2,482
13 GAT 2,267
14 NCRFpp 1,754
15 pytorch-forecasting 1,665
16 dm-haiku 1,662
17 transfer-learning-conv-ai 1,383
18 minisom 991
19 hivemind 904
20 deepxde 825
21 deep_learning_and_the_game_of_go 782
22 uncertainty-baselines 775
23 GeneticAlgorithmPython 752
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