Hands-On Transfer Learning with Python

Clustering

The unsupervised equivalent of classification is termed as clustering. These algorithms help us cluster or group data points into different groups or categories, without the availability of any output label in the input/training dataset. These algorithms try to find patterns and relationships from the input dataset, utilizing inherent features to group them into various groups based on some similarity measure, as shown in the following diagram:

Unsupervised learning: Clustering news articles

A real-world example to help understand clustering could be news articles. There are hundreds of news articles written daily, each catering ...