A large collection of ready-made LLM apps: agents, RAG systems and skills for coding agents. Every template can be run and taken apart piece by piece.
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python-machine-learning-book
Code for the first edition of Sebastian Raschka's Python Machine Learning (2015): classic algorithms in NumPy and scikit-learn, from the perceptron to clustering. A newer edition lives in a separate repo.
Who it is for
For people who want the basics of classical machine learning before neural networks.
How to start
- Open the table of contents in the README and pick a chapter, for example
ch01. - Click the
nbviewerlink next to the chapter and read the notebook in your browser. - To run it locally, follow the Python and Jupyter setup guide in
code/ch01/README.md.
Steps are taken from the README. Check the current version in the repository before running them.
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+20Sep 8 — Oct 6
Author's description
The "Python Machine Learning (1st edition)" book code repository and info resource
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