Week 2 - Collaborative Filtering

Learning Objectives

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

• Create a new Conda environment and install required Python libraries.
• Understand and apply collaborative filtering techniques, including user-based and item-based approaches, to generate personalized recommendations by leveraging user preferences, behaviors, and interactions.
• Develop and implement association rule mining and collaborative filtering techniques in Python.

Class Agenda

• Python Conda Environment Setup
• Association Rules Python Demo
• [5 min] Break
• Collaborative Filtering Slides
• Collaborative Filtering Python Demo

Task List

• Required Reading: Chapter 14.2 - Collaborative Filtering
• Complete and Submit PA1_Instacart_Recommendations on Canvas/Gradescope.

Additional Resources

• Chapter 14 Code Examples