Theory of Intelligence
MACHINE LEARNING•Unsupervised Learning•Clustering•2.5 Uses of Clustering

Introduction

Put clustering to work: customer segmentation, image segmentation by colour, and semi-supervised learning that labels thousands of examples from a handful.

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Introduction

Clustering is not just a way to draw coloured blobs on a plot. It solves real problems — often as one step inside a bigger system. This topic walks through three practical uses:

  1. customer segmentation — understand and target groups of customers;
  2. image segmentation — split an image into regions by colour;
  3. semi-supervised learning — get most of the benefit of labelled data while labelling only a few examples.

Discuss theoretical concepts, mathematical formulas, and architectural foundations.

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2.4 Other Clustering Algorithms