In this section, we will discuss various popular machine learning algorithms and how they work. We will provide examples of situations in which they work well, and when they should be avoided. The reader will learn about different machine learning algorithms and will be able to work with simple examples in scikit-learn, then scaling them with Apache Spark in the context of AWS. After completing this section, we expect readers to have a working knowledge of machine learning algorithms, and know how to implement them at scale in AWS.
This section contains the following chapters:
- Chapter 2, Classifying Twitter Feeds with Naive Bayes
- Chapter 3, Predicting House Value with Regression Algorithms
- Chapter 4, Predicting User Behavior with Tree-Based Methods
- Chapter 5, Customer Segmentation Using Clustering Algorithms ...