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py-why / dowhy

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.
https://www.pywhy.org/dowhy
MIT License
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Add links to causal inference learning resources #534

Open amit-sharma opened 2 years ago

amit-sharma commented 2 years ago

We have a stub on introduction to causality here. It will be great to add links to good books/video courses/blogs that are useful for people to get started with causality concepts.

An ideal resource is a general resource that helps people to understand the basic concepts. We are not looking for advanced books or papers.

If you are adding a resource, make sure to add a one sentence description of the resource and what people can expect to learn from it.

tusharagarwal-zomato commented 2 years ago

Currently reading this book: Causal Inference in Statistics

It is not very tough to read so far. Gives good real world examples. Takes a while to get a hang of terminology and keep a notebook handy to write down stuff as it sometimes get confusing with so many probabilities and conditional probabilities.

Divided into 4 chapters: The second chapter talks about the causal graphs and nodes and how to understand various relationships that exists between nodes by the virtue of the connections and conditioning

Chapter 3 talks about interventions and adjustemnts and other things

Chapter 4 talks about counterfactuals.