Experiment with and develop various recommendation systems using best practices and examples provided in the project.
From the README
- Evaluate: Evaluating algorithms with offline metrics.
- Model Select and Optimize: Tuning and optimizing hyperparameters for recommendation models.
- Operationalize: Operationalizing models in a production environment on Azure.
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
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recommenders has 21.8k stars on GitHub. It has been forked 3.3k times. recommenders is written mainly in Python. It has been in active development since 2018. recommenders is available under the MIT license. Its main topics are ai, artificial-intelligence, data-science, deep-learning.
What is recommenders?
Best Practices on Recommendation Systems
Is recommenders open source?
recommenders is an open-source project. It is released under the MIT license.
Is recommenders free?
Yes. recommenders is free and open source — you can use, modify and self-host it.
What license does recommenders use?
recommenders is available under the MIT license.
What language is recommenders written in?
recommenders is written mainly in Python.
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