Chapter 1 Introduction

The following content is adapted from the excellent book “Hands-on machine learning with scikit-learn, keras and tensorflow” from Géron (2019).

In this chapter you will learn how to specify a simple regression model with the tidymodels package. To use the code in this article, you will need to install the following packages:

• tidyverse
• tidymodels
• skimr
• GGally
• ggmap

library(tidyverse)
library(tidymodels)
library(skimr)
library(GGally)
library(ggmap)

In this example, our goal is to build a model of housing prices in California. In particular, the model should learn from California census data and be able to predict the median house price in any district (population of 600 to 3000 people), given some predictor variables. We use the root mean square error (RMSE) as a performance measure for our regression problem.