Deep Learning for humans
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Updated
Jul 1, 2026 - Python
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)
Trax — Deep Learning with Clear Code and Speed
Efficiently computes derivatives of NumPy code.
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.
Become a cracked AI/ML Research Engineer
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
A library for scientific machine learning and physics-informed learning
Scenic: A Jax Library for Computer Vision Research and Beyond
Mastering Diverse Domains through World Models
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