rstats

Which #TidyTuesday post offices are in Hawaii?

Use tidymodels to predict post office location with subword features and a support vector machine model.

Dimensionality reduction of #TidyTuesday United Nations voting patterns

Explore country-level UN voting with a tidymodels approach to unsupervised machine learning.

Bootstrap confidence intervals for #TidyTuesday Super Bowl commercials

Estimate how commercial characteristics like humor and patriotic themes change with time using tidymodels functions for bootstrap confidence intervals.

Getting started with k-means and #TidyTuesday employment status

Use tidy data principles to understand which kinds of occupations are most similar in terms of demographic characteristics.

Understand your models with #TidyTuesday inequality in student debt

Explore results of models with convenient tidymodels functions.

Learn tidytext with my new learnr course

I am happy to announce that this free, open source, interactive course on text mining with tidy data principles is now published!

Explore art media over time in the #TidyTuesday Tate collection dataset

Check residuals and other model diagnostics for regression models trained on text features, all with tidymodels functions.

Predicting injuries for Chicago traffic crashes

Download up-to-date city data from Chicago's open data portal and predict whether a traffic crash involved an injury with a bagged tree model.

Upcoming changes to tidytext: threat of COLLAPSE

The current development version of tidytext has changes that may affect your analyses.

Tune random forests for #TidyTuesday IKEA prices

Use tidymodels scaffolding functions for getting started quickly with commonly used models like random forests.