recommenders
Recommenders is a library of classical and deep learning algorithms used to develop recommendation systems. It offers guidance through Jupyter notebooks for data preparation, model training, hyperparameter optimization and evaluation processes. Developed under the roof of the Linux Foundation AI & Data, the project provides the tools needed to move models to the production environment.
RE
recommenders
100recommenders-team · Containers & Kubernetes
STARS22.0K
FORKS3.3K
COMMITS9.7K
CONTRIBUTORS116
VERSION1.2.1
UPDATEDtoday
PythonÖneri SistemleriMakine ÖğrenmesiData ScienceMIT
Common commercial products in this category: Docker Desktop, Red Hat OpenShift, Amazon EKS
What can it do?
- You can prepare and upload data for different suggestion algorithms.
- You can train classical and deep learning models and perform hyperparameter optimization.
- You can evaluate the models you have developed with offline metrics and take them into the production environment.
Verified against README · Oct 26, 2026 · source
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