jax

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

The Unified Machine Learning Framework

Trax — Deep Learning with Clear Code and Speed

Deep learning operations reinvented (for pytorch, tensorflow, jax and others)

Python code for "Probabilistic Machine learning" book by Kevin Murphy

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

Flax is a neural network library for JAX that is designed for flexibility.

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

JAX-based neural network library

Functional programming language for signal processing and sound synthesis

Training and serving large-scale neural networks

Fast and Easy Infinite Neural Networks in Python

Scenic: A Jax Library for Computer Vision Research and Beyond

Monte Carlo tree search in JAX

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network.