Table of Contents

 

Copyright

Brief Table of Contents

Table of Contents

Preface

Acknowledgments

About this book

About the author

About the cover illustration

1. Introduction

Chapter 1. Introduction to machine learning

1.1. What is machine learning?

1.1.1. AI and machine learning

1.1.2. The difference between a model and an algorithm

1.2. Classes of machine learning algorithms

1.2.1. Differences between supervised, unsupervised, and semi-supervised learning

1.2.2. Classification, regression, dimension reduction, and clustering

1.2.3. A brief word on deep learning

1.3. Thinking about the ethical impact of machine learning

1.4. Why use R for machine learning?

1.5. Which datasets will we use?

1.6. What will you learn in this book?

Summary

Chapter 2. Tidying, manipulating, and plotting data with the tidyverse

2.1. What is the tidyverse, and what is tidy data?

2.2. Loading the tidyverse