Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/imirzadeh/awesome-causal-inference
A (concise) curated list of awesome Causal Inference resources.
https://github.com/imirzadeh/awesome-causal-inference
List: awesome-causal-inference
artificial-intelligence causal-inference causality machine-learning
Last synced: 2 months ago
JSON representation
A (concise) curated list of awesome Causal Inference resources.
- Host: GitHub
- URL: https://github.com/imirzadeh/awesome-causal-inference
- Owner: imirzadeh
- Created: 2019-02-21T03:18:48.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2022-09-13T19:30:23.000Z (over 2 years ago)
- Last Synced: 2024-05-21T08:33:51.285Z (8 months ago)
- Topics: artificial-intelligence, causal-inference, causality, machine-learning
- Homepage:
- Size: 12.7 KB
- Stars: 207
- Watchers: 9
- Forks: 35
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-interesting-topics-in-nlp - Resource
- awesome-of-awesome-ml - awesome-causal-inference (by imirzadeh)
- Awesome-Paper-List - Causal Inference
README
# 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](#books)**
* **[Courses](#courses)**
* **[Videos and Lectures](#videos-and-lectures)**
* **[Tools](#tools)**
----
### Books
1. [The Book of Why](https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/046509760X/) by Judea Pearl, Dana Mackenzie
2. [Causal Inference Book (What If)](https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/) by Miguel Hernán, James Robins **FREE download**
3. [Causal Inference in Statistics: A Primer](https://www.amazon.com/Causal-Inference-Statistics-Judea-Pearl/dp/1119186846/) by Judea Pearl, Madelyn Glymour, Nicholas P. Jewell
4. [Elements of Causal Inference: Foundations and Learning Algorithms](https://mitpress.mit.edu/books/elements-causal-inference) by Jonas Peters, Dominik Janzing and Bernhard Schölkopf- **FREE download**
5. [Counterfactuals and Causal Inference: Methods and Principles for Social Research](https://www.amazon.com/Counterfactuals-Causal-Inference-Principles-Analytical/dp/1107694167) by Stephen L. Morgan, Christopher Winship
6. [Causal Inference Book](https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/) by Hernán MA, Robins JM **FREE download**
7. [Causality: Models, Reasoning and Inference](https://www.amazon.com/Causality-Reasoning-Inference-Judea-Pearl/) by Judea Pearl
8. [Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction](https://www.amazon.com/Causal-Inference-Statistics-Biomedical-Sciences/dp/0521885884/) by Guido W. Imbens and Donald B. Rubin
9. [Causal Inference: The Mixtape](https://www.scunning.com/mixtape.html) by Scott Cunningham **FREE download**
10. [Causal Inference for Data Science](https://www.manning.com/books/causal-inference-for-data-science) by Aleix Ruiz de Villa
---
### Courses
1. [Introduction to Causal Inference (Fall2020)](https://www.bradyneal.com/causal-inference-course) (Free)
2. [A Crash Course in Causality: Inferring Causal Effects from Observational Data](https://www.coursera.org/learn/crash-course-in-causality) (Free)
3. [Causal Inference with R - Introduction](https://www.datacamp.com/community/open-courses/causal-inference-with-r-introduction) (Free)
4. [Causal ML Mini Course](https://altdeep.ai/p/causal-ml-minicourse) (Free)
---
### Videos and Lectures
1. [Lectures on Causality: 4 Parts](https://www.youtube.com/watch?v=zvrcyqcN9Wo) by Jonas Peters
2. [Towards Causal Reinforcement Learning (CRL) - ICML'20 - Part I](https://slideslive.com/38930490/towards-causal-reinforcement-learning-crl-part-i?ref=speaker-22075-latest) By Elias Bareinboim
3. [Towards Causal Reinforcement Learning (CRL) - ICML'20 - Part II](https://slideslive.com/38930491/towards-causal-reinforcement-learning-part-ii?ref=speaker-22075-latest) By Elias Bareinboim
4. [On the Causal Foundations of AI](https://www.youtube.com/watch?v=fNuMHDrh6AY&t=31s) By Elias Bareinboim
5. [Judea Pearl: Causal Reasoning, Counterfactuals, and the Path to AGI | Lex Fridman Podcast #56](https://www.youtube.com/watch?v=pEBI0vF45ic) By Judea Pearl and Lex Fridman
6. [NeurIPS 2018 Workshop on Causal Learning](https://www.youtube.com/playlist?list=PLJscN9YDD1bu1dCKuXSV1qYmicx3g9t7A)
7. [Causal Inference Bootcamp](https://mattmasten.github.io/bootcamp/) by Matt Masten
---
### Tools
1. [DoWhy | Making causal inference easy (Python)](https://github.com/microsoft/dowhy)
2. [Ananke: A module for causal inference (Python)](https://ananke.readthedocs.io/en/latest/index.html)
3. [Causal ML: A Package for Uplift Modeling and Causal Inference with ML (Python)](https://github.com/uber/causalml)
4. [CausalNex: A toolkit for causal reasoning with Bayesian Networks (Python)](https://github.com/quantumblacklabs/causalnex)
5. [pgmpy: Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks](https://github.com/pgmpy/pgmpy)