Chapter 1: Not mtcars AGAIN

In this first case study, you will predict fuel efficiency from a US Department of Energy data set for real cars of today.

1Making predictions using machine learning

2Choosing an appropriate model

3Visualizing the fuel efficiency distribution

4Building a simple linear model

5Getting started with caret

6Training and testing data

7Training models with caret

8Evaluating your models

9Using the testing data

10Let's sample our data

11Bootstrap resampling

12Plotting modeling results

About this course

This is a free, open source course on supervised machine learning in R using the caret package. In this course, you'll work through four case studies and practice skills from exploratory data analysis through model evaluation. Ines Montani designed the web framework that runs this course, and Florencia D'Andrea helped build the site.

Contributions and comments on how to improve this course are welcome! Please file an issue or submit a pull request if you find something that could be fixed or improved.

Creative Commons License

About me

My name is Julia Silge and I'm a data scientist and software engineer at RStudio where I build modeling tools. I am both an international keynote speaker and a real-world practitioner focused on data analysis and machine learning practice. I love making beautiful charts and communicating about technical topics with diverse audiences.