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 sklearn and statsmodels.
Class Agenda
- Logistic Regression Slides
[5 min]Break (Optional)- Logistic Regression Demo
[30 min]Form Project Groups and Brainstorm Project Ideas
Task List
- Optional Reading: Chapter 6 - Multiple Linear Regression
- Required Reading: Chapter 10 - Logistic Regression
- Complete and Submit Group Project Proposal (10 Points) on Canvas.