A curated collection of resources on causality ranging from datasets, learning resources, and tools. Maintained by Shubhanshu Mishra

Resources related to causality. This awesome list is different from other lists as it tries to compile major resources related to causality in one place under different categories.

**NOTE:** This awesome list is still new and under development. Please feel free to contribute, before it can become worth sharing.

*Table of contents generated with markdown-toc*

These list contain a more focused compilation of algorithms and data related to causality under more specific categories.

- Amazon Review Sales - Google drive - Paper
- Jobs Training - Train Test - Paper
- Twins
- Synthetic IHDP
- 2016 Atlantic Causal Inference competition
- News trearment effect measurement
- Cause effect pairs
- Movie recommendations - Missing not at random (MNAR) - Paper
- CHALEARN Fast Causation Coefficient Challenge - Kaggle
- Causal inference datasets in quantitative social sciences

- Counter factual regression
- DoWhy - Microsoft Research
- Quantitative Social Science - Book
- Causal Inference using Bayesian Additive Regression Trees
- Non-parametrics for Causal Inference
- Causality by author of Causal Data Science Series (see blogs)
- InvariantCausalPrediction: Invariant Causal Prediction
- Causal Discovery Toolbox
- CausalImpact - causal inference in time series
- Daggity - Create causal graphs
- TETRAD
- ProbLog - Do-calculus

- ICML 2016 Tutorial Causal Inference for Observational Studies
- KDD 2018 Causal Inference Tutorial
- Joris Mooij ML2 Causality
- Emre Kiciman - Observational Studies in Social Media (OSSM) at ICWSM 2017
- The Blessings of Multiple Causes: A Tutorial
- Susan Athey: Counterfactual Inference (NeurIPS 2018 Tutorial) - Slides
- Ferenc Huszár Causal Inference Practical from MLSS Africa 2019 - [Notebook Runthrough] [Video 1] [Video 2]
- Causality notes and implementation in Python using statsmodels and networkX

- Causal Data Science Series
- Ferenc Huszár Series on Causal Modelling: various parts - 1, 2, 3, 4
- Diving deeper into causality Pearl, Kleinberg, Hill and untested assumptions
- Simpson’s Paradox: An Anatomy
- Simpson’s paradox and causal inference with observational data
- Causation and Correlation - Talks about possible causes for observed correlations
- (Non-)Identification in Latent Confounder Models
- Causal Inference Animated Plots - Good explanation of various causal inference methods
- Explanation, prediction, and causality: Three sides of the same coin?
- A chill intro to causal inference via propensity scores

- Causal Inference Book
- Causal Inference in statistics: A primer
- Elements of Causal Inference - Foundations and Learning Algorithms (includes code examples in R and Jupyter notebooks)
- The Book of Why: The New Science of Cause and Effect
- Causal Inference Mixtape
- Elements of Causal Inference - Foundations and Learning Algorithms

- Causal Diagrams: Draw Your Assumptions Before Your Conclusions
- Causal Inference: prediction, explanation, and intervention
- Causal Inference Experiments Short Course
- ECON 305: Economics, Causality, and Analytics [github]
- Algorithmic Information Dynamics: A Computational Approach to Causality and Living Systems From Networks to Cells
- Four Lectures on Causality by Jonas Peters

- PyData LA 2018 Keynote: Judea Pearl - The New Science of Cause and Effect
- CACM Mar. 2019 - The Seven Tools of Causal Inference
- ACM Turing Award Lecture 2011 - Judea Pearl
- Leon Bottou - Learning representations using causal invariance

- Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI
- Causality Challenge #1: Causation and Prediction
- NIPS 2013 Workshop on Causality
- ChaLearn Fast Causation Coefficient Challenge