Tune and interpret decision trees for #TidyTuesday wind turbines

Use tidymodels to predict capacity for Canadian wind turbines with decision trees.

Predicting class membership for the #TidyTuesday Datasaurus Dozen

Which of the Datasaurus Dozen are easier or harder for a random forest model to identify? Learn how to use multiclass evaluation metrics to find out.

Modeling #TidyTuesday NCAA women's basketball tournament seeds

Tune a hyperparameter and then understand how to choose the best value afterward, using tidymodels for modeling the relationship between expected wins and tournament seed.

Handle class imbalance in #TidyTuesday climbing expedition data with tidymodels

Use tidymodels for feature engineering steps like imputing missing data and subsampling for class imbalance, and build predictive models to predict the probability of survival for Himalayan climbers.

Introducing our new book, Tidy Modeling with R

An initial version of the first eleven chapters are available today! Look for more chapters to be released in the near future.

Train and analyze many models for #TidyTuesday crop yields

Learn how to use tidyverse and tidymodels functions to fit and analyze many models at once.

Build a #TidyTuesday predictive text model for The Last Airbender

Use text features and tidymodels to predict the speaker of individual lines from the show, and learn how to compute model-agnostic variable importance for any kind of model.

Get started with tidymodels and #TidyTuesday Palmer penguins

Build two kinds of classification models and evaluate them using resampling.

Supervised Machine Learning for Text Analysis in R

Announcing our new book, to be published in the Chapman & Hall/CRC Data Science Series!

Bagging with tidymodels and #TidyTuesday astronaut missions

Learn how to use bootstrap aggregating to predict the duration of astronaut missions.