deep-prob-prog-tutorials

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

Deep Learning for humans

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

? Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

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.

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

Bayesian Modeling and Probabilistic Programming in Python

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

Trax — Deep Learning with Clear Code and Speed