Week 9 - Logistic Regression

Learning Objectives

After today's class, you should be able to:

• Understand the principles of Logistic Regression, interpret model coefficients, and apply the technique to binary classification problems.
• Implement Logistic Regression models in Python using statsmodels and sklearn.

Class Agenda

• Logistic Regression Slides
• [5 min] Break (Optional)
• Logistic Regression Tutorial

Task List

• Required Reading: Chapter 10 - Logistic Regression
• Complete and Submit HW4_Logistic_Regression on Canvas.

Additional Resources

• Chapter 9 Code Examples