Training Sets, Test Sets, R, and ggplot

Learn to rigorously evaluate regression model performance with this practical course! We'll dive into using R and ggplot2 to assess how well your models generalize to new data.

This course builds upon foundational knowledge of linear and polynomial regression (as covered in my Udemy courses) and will guide you through the process of splitting data into training sets and test sets for robust model validation.

You'll gain hands-on experience with essential R programming techniques, including:

• Row-slicing data frames: Efficiently select and manipulate data subsets.
• Using the predict function in R: Generate predictions from your trained models.
• Creating informative plots with ggplot2: Mastering plot customization with clear titles and labels for effective data visualization.
• Writing for loops in R: Automate repetitive tasks for streamlined analysis.
• Developing reusable functions: Organize your code and enhance efficiency with two-variable functions.

At a comfortable pace, this course is designed to be completed in approximately two weeks. Boost your data science skills and confidently interpret your regression model results!