Gaussian Mixture Models and Expectation-Maximization (A full explanation)

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In the previous article, we described the Bayesian framework for linear regression and how we can use latent variables to reduce model complexity.

In this post, we will explain how latent variables can also be used to frame a classification problem, namely the Gaussian Mixture model (or GMM in short) that allows us to perform soft…