Python: Real World Machine Learning

Chapter 4. Clustering with Unsupervised Learning

In this chapter, we will cover the following recipes:

• Clustering data using the k-means algorithm
• Compressing an image using vector quantization
• Building a Mean Shift clustering model
• Grouping data using agglomerative clustering
• Evaluating the performance of clustering algorithms
• Automatically estimating the number of clusters using DBSCAN algorithm
• Finding patterns in stock market data
• Building a customer segmentation model

Introduction

Unsupervised learning is a paradigm in machine learning where we build models without relying on labeled training data. Until this point, we dealt with data that was labeled in some way. This means that learning algorithms can look at this data and learn to categorize them ...