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Supervised Machine Learning in R

更新时间 2026年5月
Generate, explore, evaluate, and tune the parameters of different supervised machine learning models.
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RMachine Learning25 小时3,025

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学习路径描述

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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  • Course

    1

    Machine Learning in the Tidyverse

    Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

  • Project

    额外

    Assessing the Effectiveness of Medical Treatments

    Use logistic regression to determine which treatment procedure is more effective for kidney stone removal.

Supervised Machine Learning in R
6 课程
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