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R: Machine Learning



Full course description


In this hands-on workshop you will learn how to use R to discover useful patterns in your data and to make accurate predictions. Topics will include data preparation, automated variable selection, cross-validation methods, model tuning, and several popular modeling approaches including decision trees, random forests, gradient boosting machines, and neural networks. We will use the popular tidymodels package which integrates the various steps and standardizes them across many modeling methods. This workshop takes approximately 8 hours to complete. A recommended prerequisite for this course is the R-Basics workshop.

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