Machine Learning Fundamentals in R

Learn the basics of prediction using machine learning. This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). Learn how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.

R24 hours6 Courses

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Supervised Learning in R: Classification

In this course you will learn the basics of machine learning for classification.

4 hours

Supervised Learning in R: Regression

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

4 hours

Unsupervised Learning in R

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

4 hours

Machine Learning with caret in R

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

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

Machine Learning Fundamentals in R

Loved by learners at thousands of companies

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Join over .css-1wxderj-TracksPage{color:#03ef62;}11,350,000 learners and start Machine Learning Fundamentals in R today!

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Join over 11,350,000 learners and start Machine Learning Fundamentals in R today!