Movie Recommendation engine

The data was scrapped from the TMDB API using scrappers. This project is divided into two parts:

1. Its All About Data: This section explores the every nook and cranny of the movies data set. At the end i build 2 predictive models:-
   • Regression Model that can predict the revenue of a particular movie.
   • Classification Model that identifies if a movie will be a flop or a hit.
2. Movie Recommender Systems: This part is focused around building various kinds of recommendation engines; namely the Simple Generic Recommender, the Content Based Filter and the User Based Collaborative Filter. The performance of the systems are evaluated in both a qualitative and quantitative manner.