This article is meant to explain how the K-Means Clustering algorithm works while simultaneously learning a little Python.
What is K-Means?
K-Means Clustering is an unsupervised learning algorithm that tells you how similar observations are by putting them into groups or “clusters”. K-Means is often used as a discovery step on new data to discover what various categories might be and then apply something such as a k-nearest-neighbor as a classifier to it after understanding the centroid labels. Where a centroid is the center of a “cluster” or group.