yangfa-zhang/lunax
Lunax is a machine learning framework specifically designed for the processing and analysis of tabular data.
Lunax helps data analysts and scientists rapidly build and evaluate machine learning models using structured, tabular datasets. You input raw data (like CSVs or Parquet files) and it outputs processed datasets, trained models, performance metrics, and insights into which features drive predictions. This tool is ideal for anyone who needs to quickly get from raw business data to a working predictive model.
No commits in the last 6 months. Available on PyPI.
Use this if you need a streamlined workflow to prepare tabular data, train multiple machine learning models, fine-tune their parameters, and understand their decisions with explainable AI.
Not ideal if your primary data is unstructured (like images, text, or audio) or if you require deep customization of individual model architectures beyond common tabular methods.
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Language
Python
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Last pushed
Jun 17, 2025
Commits (30d)
0
Dependencies
14
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