Movie Recommendation System

Description

Have you ever wondered how Netflix suggests movies to you based on the movies you have already watched? Or how does an e-commerce websites display options such as "Frequently Bought Together"? They may look relatively simple options but behind the scenes, a complex statistical algorithm executes in order to predict these recommendations. Such systems are called Recommender Systems, Recommendation Systems, or Recommendation Engines.

A Recommender System is one of the most famous applications of Data science and Machine learning.

There are basically three types of recommender systems explained in this notebook -

1. Demographic filtering (Simple Recommender)
2. Content-Based Filtering
3. Collaborative Filtering

Datasets used in this notebook

1. TMBD 5000 Movies dataset

2. The Movies dataset

License

MIT