/Recommendation_System_MovieLens

This repository covers a project of creating a recommendation system using collaborative filtering on the Grouplens movielens database. The surprise library is utilized to test out different models (KNN Basic, KNN Baseline, and SVD). SVD was found to be the most accurate and then was implemented into the system. The cold start problem was addressed by giving new users the opportunity to rate a random sample of 5 movies from movies that are among the most popular.

Primary LanguageJupyter Notebook

Stargazers