Gaussian Mixture Models: Likelihood and Covariance Matrix

This lecture covers the concepts of statistical independence, uncorrelatedness, and Gaussian Mixture Models. It explains how to determine correlation, independence, and conditional probabilities in different distributions. The lecture delves into the likelihood of mixtures of Gaussians, the form of the Covariance matrix for independent marginal distributions, and fitting data with single Gaussian functions.