Part 1:The Basics

This part establishes the baseline for the rest of the book. It covers all the basic topics that need to be understood to grasp the more complex concepts (and implement the workloads) that come later in the book. We begin by covering some of the fundamental concepts of AI/ML, and we discuss examples of how AI/ML is used in real-world use cases. Most importantly, we discuss common challenges that companies often run into when implementing AI/ML projects at scale and begin discussing how to address such challenges, forming the basis for deeper discussions throughout this book. Next, we outline the steps in a typical AI/ML project lifecycle, which will be used to form the overall structure of much of this book. We round out this part by introducing Google Cloud and common AI/ML tooling.

This part contains the following chapters:

• Chapter 1, AI/ML Concepts, Real-World Applications, and Challenges
• Chapter 2, Understanding the ML Model Development Life Cycle
• Chapter 3, AI/ML Tooling and the Google Cloud AI/ML Landscape