Density Estimation with Gaussian Mixture Models and Empirical Priors

Learn to estimate complex probability distributions using Gaussian Mixture Models (GMM) and empirical priors in this 18-minute educational video. Explore kernel density estimation as a foundation before diving into GMM techniques for modeling multi-modal distributions. Follow along with a practical code demonstration showing how to apply these methods to coin flip data, bridging fundamental statistical concepts with machine learning applications. Master the mathematical foundations and implementation details needed to move beyond simple parametric distributions toward more sophisticated density estimation approaches.