Part 1. Fundamentals of reactive machine learning

Reactive machine learning brings together several different areas of technology, and this part of the book is all about making sure you’re sufficiently oriented in all of them. Throughout this book, you’ll be looking at and building machine learning systems, starting with chapter 1. If you don’t have experience with machine learning, it’s important to be familiar with some of the basics of how it works. You’ll also get a flavor for all of the problems with how machine learning systems are often built in the real world. With this knowledge in hand, you’ll be ready for another big topic: reactive systems design. Applying the techniques of reactive systems design to the challenges of building machine learning systems is the core topic of this book.

After you’ve had an overview of what you’re going to do in this book, chapter 2 focuses on how you’ll do it. The chapter introduces three technologies that you’ll use throughout the book: the Scala programming language, the Akka toolkit, and the Spark data-processing library. These are powerful technologies that you can only begin to learn in a single chapter. The rest of the book will go deeper into how to use them to solve real problems.