mljar/mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
This tool helps data professionals quickly build and compare many machine learning models for predictions using structured data, like spreadsheets or database tables. You provide your dataset, and it automatically processes the data, trains various models, and identifies the best-performing one. It's designed for data scientists and analysts who need to efficiently develop predictive solutions without manually configuring every model detail.
3,246 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to rapidly develop high-performing predictive models from tabular data and want an automated way to explore different algorithms and fine-tune their settings.
Not ideal if your data is unstructured, like images or free-form text, or if you require deep, manual control over every single step of the model-building process for highly customized solutions.
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Language
Python
License
MIT
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Last pushed
Jul 07, 2025
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