The second video in a 3-part series on causality. In this video I discuss key ideas from causal inference, which aims at answering question about cause-and-effect. I finish with a concrete example with code of doing causal inference in Python.

Series Playlist:    • Causality  

📰 Read more: https://towardsdatascience.com/causal...
💻 Example code: https://github.com/ShawhinT/YouTube-B...

Resources:
The Book of Why by Judea Pearl: https://www.amazon.com/Book-Why-Scien...
Do-calculus: https://arxiv.org/abs/1210.4852
Metalearner paper: https://www.pnas.org/content/116/10/4156

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Homepage: https://shawhintalebi.com/

Introduction - 0:00
Causal Inference - 0:28
3 Gifts of Causal Inference - 1:13
Gift 1: Do-operator - 1:20
Gift 2: Confounding (deconfounded) - 3:22
Gift 3: Causal Effects - 5:51
Example: Treatment Effect of Grad School on Income - 8:05
Closing remarks - 11:12