Causal Inference | Answering causal questions
🤝 Want your team maximizing Claude? I run 1:1 and team AI workshops for companies doing $1M+ per year: https://aibuilder.academy/yt/PFBI-ZfV5rs 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://medium.com/towards-data-scien... 💻 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 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

Causal Discovery | Inferring causality from observational data

Causality: An Introduction | How (naive) statistics can fail us

Ex-Google Recruiter Explains Why "Lying" Gets You Hired

Inside Dyson’s Overengineered £1000 Hand Dryer

Causal Effects via Regression w/ Python Code

30 AI Buzzwords Explained in 30 min (for Busy Leaders)

I Hacked This Temu Router. What I Found Should Be Illegal.

Agent Skills vs MCP: What’s the difference?

AI Foundations for Business: A (non-technical) overview

Gilbert Strang: Linear Algebra, Engineering, Computer Science, AI | Hrvoje Kukina Podcast #26

Reinforcement Learning: A (practical) introduction

Nicholas Carr: The Shallows - What the Internet Is Doing to Our Brains

Normal Distributions Explained – With Real-World Examples

MAMBA and State Space Models explained | SSM explained

Quantum Mechanics: book recommendations

Brain Computer Interface w/ Python and OpenBCI for EEG data

Threads and Threading in Python

Multi-agent Systems Explained in 17 Minutes

You’re not behind (yet): What AI leaders need to know in 2026

