Movie Recommendation System

Project Overview

This project focuses on creating a movie recommendation system using user-based collaborative filtering. The system predicts ratings for unseen movies based on similar users' preferences, utilizing the Movielens 100k dataset.

Key Objectives

• Develop a recommendation system using user-based collaborative filtering.
• Compare user-based filtering with item-based collaborative filtering.
• Evaluate performance using metrics such as MSE and RMSE.

Tools Used

• Python
• Pandas
• NumPy
• Scikit-learn
• Matplotlib

Results

• Implemented user-based and item-based collaborative filtering.
• Achieved predictive insights with reasonable accuracy.
• Highlighted the strengths and limitations of both approaches.

View the Code

Click the link below to view the full code and documentation for this project on GitHub:

View on GitHub