Practical Machine Learning in R

Chapter 2Introduction to R and RStudio

Machine learning sits at the intersection of the worlds of statistics and software development. Throughout this book, we focus extensively on the statistical techniques used to unlock the value hidden within data. In this chapter, we provide you with the computer science tools that you will need to implement these techniques. In this book, we've chosen to do this using the R programming language. This chapter introduces the fundamental concepts of the R language that you will use consistently throughout the remainder of the book.

By the end of this chapter, you will have learned the following:

• The role that the R programming language plays in the world of data science and analytics
• How the RStudio integrated development environment (IDE) facilitates coding in R
• How to use packages to redistribute and reuse R code
• How to write, save, and execute your own basic R script
• The purpose of different data types in R

WELCOME TO R

The R programming language began in 1992 as an effort to create a special-purpose language for use in statistical applications. More than two decades later, the language has evolved into one of the most popular languages used by statisticians, data scientists, and business analysts around the world.

R gained rapid traction as a popular language for several reasons. First, it is available to everyone as a free, open source language developed by a community of committed developers. This approach broke the mold of past ...