LightFM is an open-source Python library designed for building and analyzing recommendation systems using hybrid matrix factorization models. It is particularly suitable for collaborative and content-based filtering approaches and is widely used in production environments for recommendation tasks, such as those found in e-commerce, content platforms, and personalized user experiences. It is aimed at data scientists, ML engineers, and developers who want a scalable, flexible, and effective way to build recommender systems.
Visit LightFM's official website for product details and getting started.
Comprehensive guide to using LightFM, including installation and examples.
Access the source code, report issues, and contribute to the LightFM project.