Chapter 8: Unsupervised Machine Learning

In the previous two chapters, you were introduced to the supervised learning class of machine learning algorithms, their real-world applications, and how to implement them at scale using Spark MLlib. In this chapter, you will be introduced to the unsupervised learning category of machine learning, where you will learn about parametric and non-parametric unsupervised algorithms. A few real-world applications of clustering and association algorithms will be presented to help you understand the applications of unsupervised learning to solve real-life problems. You will gain basic knowledge and understanding of clustering and association problems when using unsupervised machine learning. We will also look at the implementation details of a few clustering algorithms in Spark ML, such as K-means clustering, hierarchical clustering, latent Dirichlet allocation, and an association algorithm called alternating least squares.

In this chapter, we&apos...