CausalInferenceLab/Causal-Inference-with-Python

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

Notes, exercises and other materials related to causal inference, causal discovery and causal ML.

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

An index of algorithms for learning causality with data

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.

This repository consolidates my teaching material for "Causal Machine Learning".

Figures and code examples from Bayesian Analysis with Python (third edition)