Movie Recommendation

Image credit: Navdeep Singh
  • The project explores three different algorithms to recommend K movies provided that the user has already rated some movies. Utilized User-User, Item-Item Collaborative filtration and Matrix Factorization for movie recommendation.
  • The dataset used has been downloaded from Link which contained movies along with ratings according to different users. A web scraping script has been used to scrape about 780 movies from IMDB containing particulars about title, year of release, thumbnail, IMDB rating and Synopsis.
  • Web based application using Heroku by User Based collaborative filtering has been deployed here.
Apoorva Vikram Singh
Apoorva Vikram Singh
Undergraduate Student in Electrical Engineering

My research interests include Theoretical Machine Learning.