# About this book

I firmly believe that machine learning should not be the domain only of computer scientists and people with degrees in mathematics. *Machine learning with R, the tidyverse, and mlr* doesn’t assume you come from either of these backgrounds. To get the most from the book, though, you should be reasonably familiar with the R language. It will help if you understand some basic statistical concepts, but all that you’ll need is included as a statistics refresher in the appendix, so head there first to fill in any gaps in your knowledge. Anyone with a problem to solve, and data that contains the answer to that problem, can benefit from the topics taught in this book.

If you are a newcomer to R and want to learn or brush up on your basic R skills, I suggest you take a look at *R in Action*, by Robert I. Kabacoff (Manning, 2015).

This book has 5 parts, covering 20 chapters. The first part of the book is designed to get you up and running with some of the broad machine learning and R skills you’ll use throughout the rest of the book. The first chapter is designed to get your machine learning vocabulary up to speed. The second chapter will teach you a large number of tidyverse functions that will improve your general R data science skills.