quant-aq/aeromancy

⚗️ Aeromancy: A framework for performing reproducible AI and ML

30
/ 100
Emerging

Aeromancy helps machine learning practitioners and researchers ensure their experiments are fully reproducible. It takes your machine learning model code, specific dataset versions, and system environment details as inputs, producing a comprehensive, version-controlled record of how each experiment was run. This is for anyone who builds or tests machine learning models and needs to precisely replicate results or track every detail of their experimental setup.

No commits in the last 6 months.

Use this if you need to precisely track and reproduce machine learning experiments, ensuring that all details like data versions, code, and system environments are recorded.

Not ideal if you are looking for a general-purpose experiment tracker or are not using a specific software stack including Weights and Biases, Docker, Git, and PDM.

machine-learning-operations ML-experiment-tracking scientific-reproducibility data-science-workflow AI-model-development
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 7 / 25

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Stars

11

Forks

1

Language

Python

License

Apache-2.0

Last pushed

Jun 05, 2025

Commits (30d)

0

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