Gaussian Mixture Models Explained

In the world of Machine Learning, we can distinguish two main areas: Supervised and unsupervised learning. The main difference betweeen both lies in the nature of the data as well as the approaches used to deal with it. Clustering is an unsupervised learning problem where we intend to find clusters of points in our dataset that share some common characteristics. Let's suppose we have a dataset that looks like this: Our job is to find sets of points that appear close together. Please note that we are now introducing some additional notation.