k-Means Clustering (Python)

This section is a simple example of the section: Unsupervised Learning, I recommend reading the theory first before moving on to this section.

When you have unlabeled data, you may use K-means clustering, a form of unsupervised learning (i.e., data without defined categories or groups). This algorithm’s objective is to identify groups in the data; K is a variable that indicates how many groups there are. The program uses supplied attributes to iteratively assign each data point to one of K groups. Based on the similarity of their features, data points are grouped. The K-means…