Supervised Machine Learning in R

Supervised learning methods are central to your journey in data science. Learn how to generate, explore, and evaluate machine learning models by leveraging the tools in the Tidyverse. You'll learn about multiple and logistic regression techniques, tree-based models, and support vector machines. Finally, you'll learn how to tune your model's parameters for better performance.

R25 hours6 courses

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Loved by learners at thousands of companies

Machine Learning in the Tidyverse

Leverage the tools in the tidyverse to generate, explore and evaluate machine learning models.

5 hours

Intermediate Regression in R

Learn to perform linear and logistic regression with multiple explanatory variables.

4 hours

Modeling with tidymodels in R

Learn to streamline your machine learning workflows with tidymodels.

4 hours

Machine Learning with Tree-Based Models in R

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

4 hours

Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

4 hours

Hyperparameter Tuning in R

Learn how to tune your model's hyperparameters to get the best predictive results.

4 hours

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Join over .css-1osvizq-TrackShowPage{color:#03ef62;}12,380,000 learners and start Supervised Machine Learning in R today!

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Join over 12,380,000 learners and start Supervised Machine Learning in R today!