Predicting viewership for #TidyTuesday Doctor Who episodes

Using a tidymodels workflow can make many modeling tasks more convenient, but sometimes you want more flexibility and control of how to handle your modeling objects. Learn how to handle resampled workflow results and extract the quantities you are interested in.

Spatial resampling for #TidyTuesday and the #30DayMapChallenge

Use spatial resampling to more accurately estimate model performance for geographic data.

Predict #TidyTuesday giant pumpkin weights with workflowsets

Get started with tidymodels workflowsets to handle and evaluate multiple preprocessing and modeling approaches simultaneously, using pumpkin competitions.

Multiclass predictive modeling for #TidyTuesday NBER papers

Tune and evaluate a multiclass model with lasso regulariztion for economics working papers.

Dimensionality reduction for #TidyTuesday Billboard Top 100 songs

Songs on the Billboard Top 100 have many audio features. We can use data preprocessing recipes to implement dimensionality reduction and understand how these features are related.

Fit and predict with tidymodels for #TidyTuesday bird baths in Australia

In this screencast, focus on some tidymodels basics such as how to put together feature engineering and a model algorithm, and how to fit and predict.

Modeling human/computer interactions on Star Trek from #TidyTuesday with workflowsets

Learn how to evaluate multiple feature engineering and modeling approaches with workflowsets, predicting whether a person or the computer spoke a line on Star Trek.

Predict housing prices in Austin TX with tidymodels and xgboost

More xgboost with tidymodels! Learn about feature engineering to incorporate text information as indicator variables for boosted trees.

Supervised Machine Learning for Text Analysis in R is now complete

Our new book in the Chapman & Hall/CRC Data Science Series is now complete and available for preorder!

Tune xgboost models with early stopping to predict shelter animal status

Early stopping can keep an xgboost model from overfitting.