Skill Track

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.

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  • R
  • 21 hours
  • 5 courses
1
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Machine Learning in the Tidyverse

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

5 hours
Photo of Dmitriy Gorenshteyn
Dmitriy Gorenshteyn

Lead Data Scientist at Memorial Sloan Kettering Cancer Center

3
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Machine Learning with Tree-Based Models in R

In this course, you'll learn how to use tree-based models and ensembles for regression and classification.

4 hours
Photo of Gabriela de Queiroz
Gabriela de Queiroz

Data Scientist and founder of R-Ladies

Instructors

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Dmitriy Gorenshteyn

Lead Data Scientist at Memorial Sloan Kettering Cancer Center

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Ben Baumer

Assistant Professor at Smith College

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Gabriela de Queiroz

Data Scientist and founder of R-Ladies

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