625 6th Ave
New York, NY 10011United States
Thursday, September 13, 2018 - 9:00am to Friday, September 14, 2018 - 5:00pm
Learn modern machine learning with the creator of the caret package, Max Kuhn. This two-day workshop will step through the process of building, visualizing, testing and comparing models that are focused on prediction. The goal of the workshop is to provide a thorough workflow in R that can be used with many different regression or classification techniques. Case studies are used to illustrate functionality. Basic familiarity with R is required. By the end of this workshop, you should be able to easily build predictive/machine learning models in R using a variety of packages and model types. Participants will receive a copy of Max Kuhn's book, Applied Predictive Modeling. Before class everyone should install R, RStudio and the following packages. caret doParallel earth glmnet klaR recipes rpart rsample tidyposterior yardstick The workshop is broken into five parts. Part 1 Introduction Part 2 Basic Principals: Data Splitting, Models in R, Resampling, Tuning Part 3 Feature Engineering and Preprocessing: Data treatments Part 4 Regression Modeling: Measuring Performance, penalized regression, multivariate adaptive regression splines (MARS), ensembles Part 5 Classification Modeling: Measuring Performance, trees, ensembles, naive Bayes For more information please contact us.