Surprise
A Python scikit for building and analyzing recommender systems
About this project
Overview Surprise is a Python scikit for building and analyzing recommender systems that deal with explicit rating data. Surprise was designed with the following purposes in mind: — Give users perfect control over their experiments. To this end, a strong emphasis is laid on documentation, which we have tried to make as clear and precise as possible by pointing out every detail of the algorithms. — Alleviate the pain of Dataset handling. Users can use both built-in datasets (Movielens, Jester), and their own custom datasets. — Provide various ready-to-use prediction algorithms such as baseline algorithms, neighborhood methods, matrix factorization-based ( SVD, PMF, …
Technologies
Project health
GitHub
Reviews
Built by
Maintain NicolasHug/Surprise? Claiming verifies admin access through your GitHub account and gives you control of this listing.
