Lecture
This lecture covers the concept of latent variable models, focusing on the EM algorithm and Jensen's inequality. It explains the process of maximizing likelihood functions and evaluating the probability density function of a normal distribution. The lecture also discusses the role of latent variables in statistical modeling and the importance of choosing the right parameters to optimize the model.