Welcome!

Welcome to the Introduction to machine learning with {tidymodels} workshop! The course website can be found at nrennie.rbind.io/training-intro-to-tidymodels, where you will also find a copy of the slides.

Contents

In this workshop, we’ll cover:

• Using some common machine learning techniques such as Lasso regression, random forests and support vector machines.
• Fitting these models in R using {tidymodels}.
• Understanding common concepts of machine learning such as cross-validation, hyperparameter tuning and model evaluation.

Target audience

• You know a little bit of R and a little bit of statistics, don’t have any experience of machine learning but want to learn more about what it is, and how to implement models in R.

Prerequisites

• Familiarity with some statistical concepts such as correlation, variability, and simple linear regression.
• Being reasonably comfortable with data wrangling using {dplyr} and {tidyr}.

R packages

There’s no need to install these before the session, but we’ll be using the following R packages:

pkgs <- c(
  "tidymodels", "tidyverse", "glmnet", "vip",
  "ranger", "kernlab"
)
install.packages(pkgs)

Further training

View other available training courses and workshops at nrennie.rbind.io/projects/training-workshops.