jax

Deep Learning for humans

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 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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

A theoretical reconstruction of the Claude Mythos architecture, built from first principles using the available research literature.

Convert Machine Learning Code Between Frameworks

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

Efficiently computes derivatives of NumPy code.

Become a cracked AI/ML researcher/engineer with this unconventional textbook covering maths, computing, and ML with intuition.

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

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.

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

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

A library for scientific machine learning and physics-informed learning

A retargetable MLIR-based machine learning compiler and runtime toolkit.

Scenic: A Jax Library for Computer Vision Research and Beyond

Mastering Diverse Domains through World Models

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance with lower memory utilization in both training and inference.

PennyLane is an open-source quantum software platform for quantum computing, quantum machine learning, and quantum chemistry. Create meaningful quantum algorithms, from inspiration to implementation.

JAX-based neural network library

Massively parallel rigidbody physics simulation on accelerator hardware.

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

Functional programming language for signal processing and sound synthesis

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

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

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

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Monte Carlo tree search in JAX