Statistics Crystallized

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A love letter to randomness, probability, statistics, machine learning, deep learning, and econometrics—explained clearly and (occasionally) dramatically. Too many courses rush the fundamentals. Here, we slow down and master them. After studying economics at Harvard, I came to value first principles above all else. Facts and formulas fade, but logic that is deeply understood becomes ingrained; it stays with us long after the details are forgotten. This channel is built around that idea. I settled on the long-term plan for this channel: to cover several books that form the backbone of empirical reasoning and modern ML/Deep Learning: 1) Casella & Berger (CB) — Statistical Inference 2) Hernán & Robins (HR) — Causal Inference: What If 3) Bishop & Bishop (BB) — Deep Learning Possible chapter coverage order: CB 1-5, BB 1-3, CB 6-8, HR 1-3, CB 9-12, BB 4-6, HR 4-10, ... alternating BB and HR “I have no special talents. I am only passionately curious.” — Albert Einstein

Joined

2021-12-07

Format

tutorial

Topics

Educational Explainers, Science Education