/awesome-causal-inference

A (concise) curated list of awesome Causal Inference resources.

Awesome Causal Inference

A curated list of awesome Causal Inference resources.
The goal of this list is to serve a starting point for getting familiar with causality.

Table of Contents

Books

  1. The Book of Why by Judea Pearl, Dana Mackenzie
  2. Causal Inference Book (What If) by Miguel Hernán, James Robins FREE download
  3. Causal Inference in Statistics: A Primer by Judea Pearl, Madelyn Glymour, Nicholas P. Jewell
  4. Elements of Causal Inference: Foundations and Learning Algorithms by Jonas Peters, Dominik Janzing and Bernhard Schölkopf- FREE download
  5. Counterfactuals and Causal Inference: Methods and Principles for Social Research by Stephen L. Morgan, Christopher Winship
  6. Causal Inference Book by Hernán MA, Robins JM FREE download
  7. Causality: Models, Reasoning and Inference by Judea Pearl
  8. Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction by Guido W. Imbens and Donald B. Rubin
  9. Causal Inference: The Mixtape by Scott Cunningham FREE download
  10. Causal Inference for Data Science by Aleix Ruiz de Villa

Courses

  1. Introduction to Causal Inference (Fall2020) (Free)

  2. A Crash Course in Causality: Inferring Causal Effects from Observational Data (Free)

  3. Causal Inference with R - Introduction (Free)

  4. Causal ML Mini Course (Free)

Videos and Lectures

  1. Lectures on Causality: 4 Parts by Jonas Peters
  2. Towards Causal Reinforcement Learning (CRL) - ICML'20 - Part I By Elias Bareinboim
  3. Towards Causal Reinforcement Learning (CRL) - ICML'20 - Part II By Elias Bareinboim
  4. On the Causal Foundations of AI By Elias Bareinboim
  5. Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56 By Judea Pearl and Lex Fridman
  6. NeurIPS 2018 Workshop on Causal Learning
  7. Causal Inference Bootcamp by Matt Masten

Tools

  1. DoWhy | Making causal inference easy (Python)
  2. Ananke: A module for causal inference (Python)
  3. Causal ML: A Package for Uplift Modeling and Causal Inference with ML (Python)
  4. CausalNex: A toolkit for causal reasoning with Bayesian Networks (Python)
  5. pgmpy: Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks