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
Masters Student in Neural Information Processing
My research interests include Theoretical Machine Learning.