aandyw/StuffFromScratch

The birthplace of some really dubious ML/AI implementations — just for fun ツ

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Experimental

This collection provides basic, 'from scratch' implementations of machine learning models for those learning about how these algorithms work. It takes common datasets and shows the underlying code for techniques like linear regression, logistic regression, and neural networks like AlexNet and ResNet-18. Aspiring machine learning engineers or data scientists who want to understand the foundational mechanics of these models would find this useful.

No commits in the last 6 months.

Use this if you are a machine learning student or practitioner looking to understand the core mathematical and computational mechanics of various ML algorithms without relying on high-level libraries.

Not ideal if you need production-ready code, highly optimized implementations, or cutting-edge research models.

machine-learning-education algorithm-understanding deep-learning-fundamentals computer-vision-basics data-science-learning

No License Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 4 / 25

Maturity 8 / 25

Community 0 / 25

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