google-research/recsim
A Configurable Recommender Systems Simulation Platform
This platform helps researchers and practitioners simulate how users interact with recommendation systems over time. You provide details about user preferences, item characteristics, and how users might respond, and it generates simulated interaction data. This is for machine learning researchers and recommendation system developers who need to test new algorithms in a controlled environment.
782 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are developing or researching new recommendation algorithms and need a flexible way to simulate user behavior and system responses before deploying to real users.
Not ideal if you need an out-of-the-box recommendation system for immediate deployment, or if you're not deeply involved in algorithm research and development.
Stars
782
Forks
133
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 03, 2022
Commits (30d)
0
Dependencies
7
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