Week 8 - Naive Bayes
Learning Objectives
After today's class, you should be able to:
- Understand the probabilistic Naive Bayes algorithm for classification tasks, including how it models feature likelihoods using Bayes’ Theorem with a conditional independence assumption.
- Calculate probabilities, develop and implement Naive Bayes models in Python.
Class Agenda
[30 min]Exam 1 Results- Naive Bayes Slides
[5 min]Break (Optional)- KNN Demo
[30 min]Python Q&A/Debugging Help
Task List
- Required Reading: Chapter 8 - The Naive Bayes Classifier
- Complete and Submit HW5_Naive_Bayes on Canvas.