donnemartin/data-science-ipython-notebooks resource

Health v2 · maintenance only

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29326 stars · 8027 forks observed · 2026-08-28

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

A large curated collection of IPython/Jupyter notebooks covering data science topics including deep learning (TensorFlow, Keras, Theano, Caffe), scikit-learn, pandas, NumPy, matplotlib, Spark/Hadoop big data, Kaggle analyses, and AWS. It serves as a hands-on tutorial resource rather than a software library.

Use cases

• learn deep learning with tensorflow and keras through notebooks
• jupyter notebook tutorials for pandas and numpy
• learn scikit-learn machine learning by example
• spark and hadoop big data notebook examples
• kaggle competition starter notebooks
• learn matplotlib data visualization in python
• aws and big data tutorials for data scientists

When to choose

• you want hands-on, runnable notebook tutorials across the Python data science stack
• you are learning deep learning, pandas, scikit-learn, or Spark by example
• you need curated links to quality tutorials in one place

When to avoid

• you need a production-ready library or tool rather than educational material
• you need up-to-date coverage of the latest framework versions, as some notebooks reference older APIs
• you want a structured course with assessments instead of reference notebooks

Facets

learning-resource · maturity maintenance

machine-learning deep-learning data-science data-visualization data-science machine-learning deep-learning big-data tutorials python cross-platform ipython-notebooks jupyter tensorflow keras scikit-learn pandas numpy spark kaggle aws educational-notebooks

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For agents

markdown · JSON · MCP: product_card(name="donnemartin/data-science-ipython-notebooks")