Summary
In this chapter, you got an overview of the basic concepts of ML. You went over the definition of ML and how it differs from typical software. You also learned about important terminologies and concepts that are heavily used in the context of ML. The chapter also covered the important steps of the ML life cycle, which can be combined together to create an end-to-end ML pipeline to deploy models in production. Lastly, you got an introduction to the AWS ML stack and how the AWS AI/ML services are organized.
In Chapter 2, Exploring Key AWS Machine Learning Services for Healthcare and Life Sciences, we will dive into the details of some of the critical AWS services that allow healthcare and life sciences customers to build, train, and deploy ML models for solving important problems in the industry. We will cover those problems in detail in the subsequent chapters of this book.
