Part 3 Intermediate steps

Part 3 is focused on intermediate steps. Chapter 9 overviews the learning curve analysis, provides a closer look at the residual analysis, and helps in finding commonalities in residuals. Chapter 10 is dedicated to training pipelines, covers tools and platforms we can use to build and maintain training pipelines, and presents such topics as scalability and configurability of training pipelines. Chapter 11 addresses features and feature engineering, analyzes features, gives hints on selecting appropriate features for the ML model, and lists pros and cons of feature stores. In chapter 12, we give an overview on measuring and reporting results and discuss the benefits of conducting A/B tests.