Movie Recommender System

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:

1. Simple Recommender
2. Correlation Recommender
3. Content-Based Recommender
4. Collaborative Filtering
5. Hybrid Recommender

Intructions

Since one of the datasets cannot be uploaded due to its big size, the instructions have been provided in the netflix folder.