PCA and UMAP with tidymodels and #TidyTuesday cocktail recipes
Use tidymodels for unsupervised dimensionality reduction.
Machine learning, text analysis, and more
Use tidymodels for unsupervised dimensionality reduction.
Measure how the frequency of some feature differs across some group or set, using the weighted log odds.
Learn how to tune hyperparameters for an XGBoost classification model to predict wins and losses.
I am happy to announce that a new version of my free, online, interactive course has been published!
Lately I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to evaluate complex models. Today’s screencast demonstrates how to implement multiclass or multinomial classification using with this week’s #TidyTuesday dataset on volcanoes. 🌋 Here is the code I used in the video, for those who prefer reading instead of or in addition to video. Explore the data Our modeling goal is to predict the type of volcano from this week’s #TidyTuesday dataset based on other volcano characteristics like latitude, longitude, tectonic setting, etc.