Stanford CS229 Machine Learning | Spring 2026 | Lecture 6: Dataset Split, ML Advice
Stanford Online · 78:26
This lecture treats the central ML problem—how to pick a model that generalizes from a finite noisy sample—as a three-term error budget (irreducible noise, bias², variance), then shows regularization, holdouts/cross-v...