davidrpugh/machine-learning-for-tabular-data

Repository of course materials for a multi-day course on machine learning for tabular data using Scikit-Learn and XGBoost

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Established

This project provides practical, hands-on course materials for applying machine learning to structured, tabular data. It guides users through building complete machine learning pipelines using tools like Scikit-Learn and XGBoost, from initial data preparation to model deployment. Scientists, engineers, and data analysts who work with structured datasets to solve real-world problems will benefit from this resource.

Use this if you need to build, train, and deploy machine learning models using structured tabular data to solve science and engineering problems.

Not ideal if your primary focus is on deep learning for unstructured data like images or text.

data-analysis predictive-modeling engineering-applications scientific-research business-intelligence
No Package No Dependents
Maintenance 10 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

52

Forks

15

Language

Jupyter Notebook

License

BSD-3-Clause

Last pushed

Feb 19, 2026

Commits (30d)

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