Part 1. The machine-learning workflow
In this first part of the book, we introduce the basic machine-learning workflow. Each chapter covers one step of the workflow.
Chapter 1 introduces machine learning, what it’s useful for, and why you should be reading this book.
In chapter 2, you’ll dive into the data-processing step of the basic ML workflow. You’ll look at common ways to clean up and extract value from real-world and messy data.
In chapter 3, you’ll start building simple ML models as you learn about a few modeling algorithms and how they’re used in common implementations.
In chapter 4, you’ll take a deeper look at our ML models to evaluate and optimize their performance.
Chapter 5 is dedicated to basic feature engineering. Extracting ...
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