amueller/introduction_to_ml_with_python resource

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8161 stars · 4670 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Companion repository of Jupyter notebooks and the mglearn helper library for the O'Reilly book 'Introduction to Machine Learning with Python' by Andreas Mueller and Sarah Guido. It provides runnable examples, datasets, and figure-generation code built on scikit-learn, numpy, pandas, and matplotlib.

Use cases

• learn machine learning with scikit-learn through notebooks
• follow along with the Introduction to Machine Learning with Python book
• find beginner-friendly ML code examples in Python
• get helper functions for plotting ML figures and datasets
• run ML tutorials interactively in Jupyter or Binder

When to choose

• you are learning scikit-learn and want worked notebook examples
• you are reading the book and want the accompanying code and datasets
• you want simple illustrative plots of ML concepts like decision trees and cross-validation

When to avoid

• you need a production-ready ML library or framework
• you need up-to-date examples for the latest scikit-learn versions
• you need a maintained tool with a license for redistribution

Facets

learning-resource · maturity maintenance

machine-learning data-science data-visualization machine-learning data-science education tutorials python cross-platform jupyter-notebooks scikit-learn book-companion mglearn educational

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