25 Overview

Now that you are equipped with powerful programming tools we can finally move into the world of applied modeling. In this module we’ll build on your new tools of data wrangling and programming to fit, analyze, and evaluate predictive models.

25.1 Learning objectives

By the end of this module you should be able to:

• Split your data into training and test sets.
• Instantiate, train, fit, and evaluate a basic predictive model.
• Apply feature engineering steps to preprocess numeric and categorical data.
• Perform resampling and hyperparameter grid searche procedures for robust model evaluation and selection.

25.2 Estimated time requirement

The estimated time to go through the module lessons is about 3-4 hours.

25.3 Tasks

• Work through the 3 module lessons.
• Upon finishing each lesson take the associated lesson quizzes on Canvas. Be sure to complete the lesson quiz no later than the due date listed on Canvas.
• Check Canvas for this week’s lab, lab quiz due date, and any additional content (i.e. in-class material)