I'll be conducting a workshop called "Applied Machine Learning" in Washington DC on August 15 and 16. The last one, at the RStudio conference, sold out quickly.
The 2 day course is a blend of caret and the newer tidy modeling pacakges (recipes, rsample, etc):
Machine learning is the study and application of algorithms that learn from and make predictions on data. From search results to self-driving cars, it has manifested itself in all areas of our lives and is one of the most exciting and fast-growing fields of research in the world of data science.
This two-day course will provide an overview of using R for supervised learning. The session will step through the process of building, visualizing, testing, and comparing models that are focused on prediction. The goal of the course is to provide a thorough workflow in R that can be used with many different regression or classification techniques. Case studies on real data will be used to illustrate the functionality and several different predictive models are illustrated.
The course focuses on both high-level approaches to modeling (e.g., the caret package) and newer modeling packages in the tidyverse: recipes, rsample, yardstick, and tidyposterior. Basic familiarity with R and the tidyverse is required.