neural-tangents

A curated list of awesome Deep Learning tutorials, projects and communities.

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

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

A Python library that helps data scientists to infer causation rather than observing correlation.

A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow

PyMC educational resources