Hands-On Recommendation Systems with Python

Clustering

One of the main ideas behind collaborative filtering is that if user A has the same opinion of a product as user B, then A is also more likely to have the same opinion as B on another product than that of a randomly chosen user.

Clustering is one of the most popular techniques used in collaborative-filtering algorithms. It is a type of unsupervised learning that groups data points into different classes in such a way that data points belonging to a particular class are more similar to each other than data points belonging to different classes:

For example, imagine that all our users were plotted on a two-dimensional Cartesian plane, ...