Movie Recommendation System using Collaborative Filtering

Movie recommendation system is a publicly demanding system as everyone wants to easily view and land upon their interests. A Movie recommendation system uses past records of people to recommend them movies similar to their previous interests. It provides a new way to find things of our interest. It predicts interests of users by studying their previous preferences. It analyzes them and suggests best movies to watch at that time. It also sorts movies according to its ratings. In this project, we are building this system using collaborative filtering algorithm to provide an efficient user interface. User experience of movie streaming platforms will enhance by usage of this system as it will ease the process of searching desired movies. The similarity metrics generated using the data of users, movies items and their ratings help for providing recommendations. For users, it will also find unknown movies having similarities with their interests.