RecNexa

RecNexa is a production-oriented collection of recommendation algorithms, designed to curate and integrate practical implementations in a consistent, maintainable way.

The project focuses on algorithm packages from the third-party community, especially valuable implementations that are no longer maintained. Where needed, it adapts and maintains them for use in modern production environments.

Included Algorithms

  • rankfm: A factorization machine implementation optimized for ranking. See the rankfm documentation.

Coming Soon

  • LightSANs: A sequential recommendation algorithm implementation, currently being prepared.

Roadmap

RecNexa will continue to collect more proven recommendation algorithms, gradually covering additional recommendation scenarios and modeling paradigms.

Installation, configuration, usage examples, and API references for each algorithm are maintained separately in the docs directory. This README only introduces the project and its included algorithms.

License

This project is licensed under GPL-3.0-only.

Key dates

PyPI data
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  • Released:
Newer release available (0.2.0)

1 maintainer

PyPI data
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License expression

GPL-3.0-only
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Requires

Python >=3.11

Provides Extra

dev rankfm all

Tags

collaborative-filtering factorization-machines implicit-feedback recommendation ranking

Classifiers

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