Recent Articles
Max Kuhn
The first version of discrim (0.0.1) is on CRAN. Read more ...
2019/10/17
Max Kuhn
A major update to the tuning parameter package. Read more ...
2019/10/01
Jim Hester
Make package development easier by providing R functions that simplify and expedite common tasks. Read more ...
2019/09/26
Hadley Wickham
2019/09/13
Gábor Csárdi
We use callr::r_session to implement a worker pool and task queue in 100 lines of R code. Read more ...
2019/09/09
Mara Averick and Hadley Wickham
Reflections on tidyverse dev day at useR! 2019. Read more ...
2019/09/06
Hadley Wickham
2019/09/05
Max Kuhn, Edgar Ruiz, and Davis Vaughan
The latest updates to the tidymodels packages Read more ...
2019/09/05
Jim Hester
gmailr v1.0.0 is on CRAN. Read more ...
2019/08/26
Jenny Bryan
gargle is now on CRAN. Read more ...
2019/08/20
Upcoming events
London
Nov 18 - Nov 19
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 class is taught by Max Kuhn.