A recommender system built using the movie lens dataset and trained using LightFM
The MovieLens dataset is a collection of movie ratings and related metadata that was initially compiled by the GroupLens research group at the University of Minnesota. It consists of over 27,000 movies and 20 million ratings from around 138,000 users. The dataset includes user ratings, demographic information, movie genres, release year, and other movie attributes. The data was collected over several years starting in the late 1990s and was made available to the public as part of a research project. The MovieLens dataset has been widely used in research and industry to develop and evaluate recommendation systems and other machine learning algorithms for movie rating prediction, personalized recommendation, and more.