Chapter 7: Supervised Machine Learning
In the previous two chapters, you were introduced to the machine learning process, the various stages involved, and the first step of the process, namely feature engineering. Equipped with the fundamental knowledge of the machine learning process and with a usable set of machine learning features, you are ready to move on to the core part of the machine learning process, namely model training.
In this chapter, you will be introduced to the supervised learning category of machine learning algorithms, where you will learn about parametric and non-parametric algorithms, as well as gain the knowledge required to solve regression and classification problems using machine learning. Finally, you will implement a few regression algorithms using the Spark machine learning library, such as linear regression and decision trees, and a few classification algorithms such as logistic regression, naïve Bayes, and support vector machines. Tree ensemble...