Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA

Name: Stanford CS229 Machine Learning | Spring 2026 | Lecture 10: GMM (EM), PCA
Uploaded: 2026-07-31T00:00:00.000Z
Duration: 1 h 20 min 5 s
Description: This CS229 lecture derives the EM algorithm as a general method for latent-variable models—recovering last class’s ad hoc Gaussian mixture updates as a special case—and then treats PCA as the non-probabilistic analog:...

Stanford Online · 80:05

This CS229 lecture derives the EM algorithm as a general method for latent-variable models—recovering last class’s ad hoc Gaussian mixture updates as a special case—and then treats PCA as the non-probabilistic analog:...

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