patrickloeber/MLfromscratch resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1641 stars · 576 forks observed · 2026-08-28

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

A Python repository implementing classic machine learning algorithms (KNN, SVM, decision trees, K-Means, PCA, etc.) from scratch using only NumPy. It accompanies a YouTube tutorial series explaining the math and code behind each algorithm.

Use cases

• learn how machine learning algorithms work internally
• implement KNN from scratch in python
• understand the math behind SVM and logistic regression
• study a from-scratch decision tree implementation
• teach an intro ML course with simple code examples
• compare naive implementations against scikit-learn

When to choose

• you want to understand ML algorithms at a fundamental level
• you prefer learning via code paired with video explanations
• you need simple, readable reference implementations for study or teaching

When to avoid

• you need production-ready, optimized, or feature-complete ML tooling
• you want GPU acceleration or large-scale training
• you need algorithms beyond the small set covered here

Facets

learning-resource · maturity maintenance

machine-learning data-science machine-learning education tutorials python cross-platform from-scratch educational numpy algorithms tutorial-code

Member repositories

For agents

markdown · JSON · MCP: product_card(name="patrickloeber/MLfromscratch")