Explore the evolution of art media in the Tate collection through a 42-minute tutorial on training regularized regression models with text features using tidymodels. Learn to analyze changes in artistic mediums over time, perform model diagnostics, and interpret results. Dive into data preprocessing, token filtering, feature engineering, and variable importance. Discover how to visualize predictions, assess model performance, and gain insights into artistic trends. Access accompanying code on Julia Silge's blog for hands-on practice and further exploration.