polyaxon/traceml

Engine for ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.

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Verified

This project helps machine learning engineers and data scientists keep track of their experiments. It allows you to log the various inputs, configurations, metrics, and data references that go into training a model. You can then visualize and explain model behavior, detect drift in data, and create dashboards to monitor performance. This is ideal for anyone working with machine learning models who needs to organize, compare, and understand their experiments.

530 stars and 133,461 monthly downloads. Used by 1 other package. Actively maintained with 6 commits in the last 30 days. Available on PyPI.

Use this if you need a centralized system to log, visualize, and compare your machine learning experiments and the data that feeds them.

Not ideal if you are looking for a general-purpose data visualization tool unrelated to machine learning experiment tracking.

machine-learning-operations model-training experiment-tracking data-science ML-experimentation
Maintenance 20 / 25
Adoption 21 / 25
Maturity 25 / 25
Community 16 / 25

How are scores calculated?

Stars

530

Forks

47

Language

Python

License

Apache-2.0

Last pushed

Mar 24, 2026

Monthly downloads

133,461

Commits (30d)

6

Reverse dependents

1

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curl "https://pt-edge.onrender.com/api/v1/quality/mlops/polyaxon/traceml"

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