Evaluating Model Predictions for Regression Models

How do you know if a regression model is a good estimator of what you are trying to predict?
This lab will walk you through building several multivariate linear regression models using different prediction variables and then comparing the model predictions using evaluation tools such as R-squared and Mean Squared Error (MSE).

Learning Objectives

Upon completion of this lab you will be able to:

• Import data using pandas
• Prepare data for modeling
• Build a regression model using scikit-learn
• Evaluate the regression model using statistics such as R² and mean squared error
• Compare multiple models using regression evaluation metrics

Intended Audience

This lab is intended for:

• Machine learning engineers
• Anyone interested in evaluating machine learning model performance

Prerequisites

You should possess:

• A basic understanding of Python