elehcimd/mltraq

Track and Collaborate on ML & AI Experiments.

38
/ 100
Emerging

This tool helps machine learning and AI developers organize, run, and share their experimental work. It takes your experiment parameters, code, and results as input, providing a structured way to track what you've done. This is designed for ML/AI developers who are constantly iterating on models and need to keep their work reproducible and easy to share with teammates.

No commits in the last 6 months. Available on PyPI.

Use this if you are an ML/AI developer who needs to systematically track different versions of your models, data, and training runs to ensure reproducibility and facilitate collaboration.

Not ideal if you are a non-technical user looking for a low-code platform to build or deploy ML models without needing to manage underlying experimental details.

machine-learning-engineering ai-development experiment-tracking ml-model-management data-science-workflow
Stale 6m
Maintenance 0 / 25
Adoption 8 / 25
Maturity 25 / 25
Community 5 / 25

How are scores calculated?

Stars

44

Forks

2

Language

Jupyter Notebook

License

BSD-3-Clause

Last pushed

Mar 10, 2025

Commits (30d)

0

Dependencies

8

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