Week 7 - k-Nearest Neighbors

Learning Objectives

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

• Understand the k-Nearest Neighbor (kNN) algorithm for classification tasks, enabling the extraction of insights by analyzing patterns in labeled data.
• Develop and implement KNN models in Python.

Class Agenda

• k-Nearest Neighbors Slides
• [5 min] Break (Optional)
• KNN Demo
• [30 min] Python Q&A/Debugging Help

Task List

• Required Reading: Chapter 7 - k-Nearest Neighbors (k-NN)
• Complete and Submit HW4_k-Nearest_Neighbors on Canvas/Gradescope.

Additional Resources

• Chapter 7 Code Examples