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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

  • Courses

  • Videos and Lectures

  • Tools


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

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