56:38

26. Gaussian Mixture Models

51:42

4. Stochastic Gradient Descent

30:49

The EM Algorithm Clearly Explained (Expectation-Maximization Algorithm)

41:52

9. Lagrangian Duality and Convex Optimization

1:11:21

CMU Advanced NLP 2022 (23): Latent Variable Models

53:48

11. Subgradient Descent

24:08

EM Algorithm : Data Science Concepts

1:26:40

Stanford CS229 I K-Means, GMM (non EM), Expectation Maximization I 2022 I Lecture 12