fusion-jena/MLProvLab
Provenance Management for Data Science Notebooks
This tool helps data scientists and researchers keep track of their machine learning experiments within JupyterLab. It automatically records datasets, variables, and code used in your notebooks, showing how they connect across different cells. This allows you to compare various runs of your experiments, making it easier to understand outcomes and improve your models.
No commits in the last 6 months. Available on PyPI.
Use this if you need to understand, compare, and reproduce the steps and data flow in your machine learning experiments conducted in JupyterLab.
Not ideal if your workflow primarily involves traditional software development or command-line scripting outside of Jupyter notebooks.
Stars
14
Forks
3
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 02, 2021
Commits (30d)
0
Dependencies
1
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