A Quick Tour of Tidymodels
A Quick Tour of Tidymodels


In this 90 minute tutorial, we'll get a brief demonstration of how modeling is conducted in the tidyverse. Using an example data set, we'll walk though the process of pre-processing and feature engineering of data, model fitting and tuning, and performance estimation.

The workshop assumes that you have used simple R modeling functions (like `lm()`) and basic tidyverse functions. You don't need to be an expert. The materials will be on GitHub and we'll have RStudio servers that you can use if you can't (or don't want to) install anything locally.


Max was a nonclinical statistician for 12 years in the pharmaceutical industry and for 6 years in the medical diagnostic industry. His degrees are in Biostatistics (Ph.D.) and Mathematics (B.S.). He has released several R packages for predictive modeling and machine learning, including caret, C50, and Cubist. He is the author of the Springer book Applied Predictive Modeling (with Kjell Johnson), which won the American Statistical Association’s Ziegel Award for best book in 2014.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google