machine-learning-visualized
A Jupyter Book that implements machine learning algorithms in NumPy and derives the math from first principles. Meant for learners who want to understand how the algorithms work.
Share on XLicense: MIT
Overview
Machine Learning Visualized is a Jupyter Book that teaches machine learning algorithms by deriving them from first principles in Jupyter Notebooks with NumPy. The output of each notebook is a visualization of the algorithm during training, ending at its optimal weights. There are also interactive notebooks built with Marimo that show how weights affect loss functions. This repository only holds the code that configures and builds the book, while each algorithm has its own separate repository.
Key features
- Notebooks that derive algorithms mathematically with NumPy
- Visualizes training until the weights converge
- Interactive Marimo notebooks showing weights against loss
- Builds a website from Markdown and notebooks with Jupyter Book
Best for
Learners who want to see how ML algorithms work step by step rather than call a library. The algorithm code itself lives in separate repositories.
- Upstream
- gavinkhung/machine-learning-visualized
- Fork on GitHub
- Guo-astro/machine-learning-visualized
- Upstream stars
- 2.1k
- Category
- Learning, interviews and curated lists
- Language
- TeX
- License
- MIT
- Forked
- 2026-08-11
- Sync status
- In syncLast synced 2026-10-16
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