Entertainment Recommendation System

Abstract

For each of us, entertainment is a necessity for recharging our spirits and recharging our batteries. Also, entertainment restores our confidence in the workplace, allowing us to work more enthusiastically. Recommendation systems help you surface the things users love. Thus, we intend to make a recommender system that would be capable of recommending the users the movies, music, books, and games on their search and the popularity of the movie and the song all in one and basically completing the user needs and saving his time simultaneously. We intend to make a website that fetches all the latest movies and songs through an API, recommends the user the most related content based on their searches, and based on the genre of the movie or music the user searched for. Our recommendation models will use different filtering techniques like Content-Based Filtering and Collaborative Filtering and Through this system, the user will find it easy and interesting to search for their entertainment content.