Stanford CS221 | Autumn 2025 | Lecture 14: Bayesian Networks and Learning
Stanford Online · 80:30
This lecture shows how to learn Bayesian-network parameters from data: with fully observed variables, maximum likelihood reduces to count-and-normalize (optionally with Laplace smoothing and parameter sharing); with m...