Explore subword features in machine learning for text analysis through a practical demonstration using tidymodels to predict Hawaiian post offices based on their names. Learn how to work with the #TidyTuesday dataset, preprocess text data, implement a recipe for feature engineering, tune hyperparameters, and apply a linear SVM model. Gain insights into evaluating model performance through metrics and estimates, all while following along with the code available on Julia Silge's blog.