This was the final project for Data Science with Python (CS677) course at Boston University. It focused on exploring 3 movie datasets consisting of unique users, movies, ratings, genres and keywords. The purpose of the project was to conduct an analysis on the movies and showcase 5 different types of recommender systems and how they differ from each other:
- Simple Recommender
- Correlation Recommender
- Content-Based Recommender
- Collaborative Filtering
- Hybrid Recommender
Since one of the datasets cannot be uploaded due to its big size, the instructions have been provided in the netflix folder.