kakao/buffalo
TOROS Buffalo: A fast and scalable production-ready open source project for recommender systems
When you have a large catalog of items and customer interactions, this project helps you suggest relevant products, content, or services to your users. It takes in past user behavior data (like purchases or views) and outputs personalized recommendations. E-commerce managers, content strategists, and product owners for digital services would use this to enhance user experience and engagement.
581 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to build a high-performance recommendation engine that can quickly process many user preferences and item interactions, even with limited hardware.
Not ideal if your primary goal is to perform deep, academic research into novel recommendation algorithms rather than deploy a production-ready system.
Stars
581
Forks
109
Language
Python
License
Apache-2.0
Category
Last pushed
May 16, 2025
Commits (30d)
0
Dependencies
4
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