dm4ml/gate

Drift detection module for machine learning pipelines.

30
/ 100
Emerging

When you're running machine learning models in production, the data your models see can subtly change over time, leading to inaccurate predictions. This tool monitors your live data streams, whether they are traditional tables or complex AI embeddings, and alerts you when significant, unexpected shifts occur. It's for data scientists, MLOps engineers, and anyone responsible for maintaining the accuracy and reliability of deployed machine learning systems.

No commits in the last 6 months.

Use this if you need to automatically detect when the input data to your machine learning models has changed in a way that could impact performance, reducing false alarms.

Not ideal if you need to interpret the root cause of data quality issues or monitor individual data points rather than overall data distribution changes.

MLOps data-quality model-monitoring production-AI data-drift
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 7 / 25

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Stars

25

Forks

2

Language

Python

License

MIT

Last pushed

Jun 21, 2023

Commits (30d)

0

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