Chapter 4
Unsupervised Learning
Section 3
Mixture of Gaussians Clustering
Explain how the mixture of Gaussians clustering algorithm works, how it is different from k-means clustering, and how the EM-algorithm is used to learn the clusters - Explain the underlying assumptions of mixture of Gaussians clustering, that is, how clusters are represented as Gaussian distributions - Explain how a mixture of Gaussians clustering is different from the simpler k-means clustering algorithm from the previous video - Explain how the EM-algorithm is used to actually learn the mixture of Gaussians clusters