Chapter 1. Learning reactive machine learning
This chapter covers
- Introducing the components of machine learning systems
- Understanding the reactive systems design paradigm
- The reactive approach to building machine learning systems
This book is all about how to build machine learning systems, which are sets of software components capable of learning from data and making predictions about the future. This chapter discusses the challenges of building machine learning systems and offers some approaches to overcoming those challenges. The example we’ll look at is of a startup that tries to build a machine learning system from the ground up and finds it very, very hard.
If you’ve never built a machine learning system before, you may find it challenging and a bit confusing. My goal is to take some of the pain and mystery out of this process. I won’t be able to teach you everything there is to know about the techniques of machine learning; that would take a mountain of books. Instead, we’ll focus on how to build a system that can put the power of machine learning to use.