This is a repository for a Movie Recommendation System using a parsed version of MovieLens 'ml-latest' dataset, which contains 27,000,000 ratings and 1,100,000 tag applications applied to 58,000 movies by 280,000 users. The system uses a Singular Value Decomposition algorithm to create a model of the user and movie data in order to predict recommendations.
The movie recommendations, updated with the latest users, can be found in the recommendations.csv. Feel free to modify parse.py to parse your own custom datasets based on the 27M 'ml-latest' file. The file test.py is where the dataset is loaded and the algorithm run.