Data Science, Unsupervised Learning, Machine Learning, Gaussian Mixture Model, Coding.
Introduction The Expectation-Maximization Algorithm, or EM algorithm for short, is an approach for maximum likelihood estimation in the presence of latent variables. The EM algorithm was explained and given its name in a classic 1977 paper by A. Dempster and D. Rubin in the Journal of the Royal