Deep Learning with PyTorch Quick Start Guide

Clustering

This is the most straightforward unsupervised method. In many cases, it does not matter that the data is unlabeled; what we are interested in is the fact that the data clusters around certain points. Recommender systems that, say, recommend movies or books from an online store often use clustering techniques. An approach here is for an algorithm to analyze a customer's purchase history, comparing it to other customers, and making recommendations based on similarities. The algorithm clusters customers' usage patterns into groups. At no time does the algorithm know what the groups are; it is able to work this out for itself. One of the most used clustering algorithms is k-means. This algorithm works by establishing cluster centers ...