Detecting Patterns with Unsupervised Learning

In this chapter, we are going to learn about unsupervised learning and how to use it in real-world situations. By the end of this chapter, you will have a better understanding of the following topics:

• Unsupervised learning definition
• Clustering data with the K-Means algorithm
• Estimating the number of clusters with the Mean Shift algorithm
• Estimating the quality of clustering with silhouette scores
• Gaussian Mixture Models
• Building a classifier based on Gaussian Mixture Models
• Finding subgroups in stock markets the using Affinity Propagation model
• Segmenting the market based on shopping patterns