geohot/ai-notebooks resource

Health v2 · maintenance only

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Adoption not part of the score

1425 stars · 218 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter notebooks by George Hotz implementing simple AI and machine learning algorithms in Python 3 using TensorFlow 2, PyTorch, and Keras. It is intended as an educational reference designed for viewing on GitHub.

Use cases

• learn how ML algorithms work from scratch
• study neural network implementations in pytorch and tensorflow
• find example notebook implementations of AI algorithms
• reference simple deep learning code while learning
• explore educational machine learning experiments

When to choose

• you want readable, minimal implementations of AI algorithms for learning
• you prefer notebook-style tutorials over full libraries
• you want to compare implementations across TensorFlow, PyTorch, and Keras

When to avoid

• you need production-ready, tested, or maintained ML code
• you require a licensed dependency for commercial use (no license is provided)
• you need a packaged library with an API rather than example notebooks

Facets

learning-resource · maturity maintenance

machine-learning deep-learning data-science machine-learning deep-learning artificial-intelligence tutorials python cross-platform jupyter-notebooks tensorflow pytorch keras educational algorithms

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markdown · JSON · MCP: product_card(name="geohot/ai-notebooks")