recommenders
Discover comprehensive insights into recommendation systems, covering algorithmic approaches like collaborative filtering and deep learning. Access Jupyter notebooks offering practical examples for data preparation, model development, and result evaluation, optimized under the support of the Linux Foundation. Learn about Recommenders version 1.2.0 for streamlined performance across modern Python versions. Suitable for researchers and developers looking to optimize recommendation system deployment from prototype to production.
