ml-cube/ml3-drift
Easy-to-embed Drift Detectors
When your machine learning models are deployed, their performance can degrade over time due to changes in the real-world data they encounter. This tool helps Data Scientists and MLOps Engineers automatically detect these "data drifts" by comparing incoming data to a reference dataset. It tells you when your model's input or output data has significantly changed, helping you maintain model accuracy and reliability.
No commits in the last 6 months.
Use this if you need to continuously monitor the input or output data of your deployed machine learning models for unexpected changes in their statistical properties.
Not ideal if you are looking for a tool to develop or train new machine learning models, as this focuses specifically on monitoring existing models.
Stars
46
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 10, 2025
Commits (30d)
0
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