DorsaRoh/Machine-Learning resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2447 stars · 194 forks observed · 2026-08-28

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

A collection of Jupyter Notebook tutorials implementing machine learning models from scratch using only NumPy. It covers neural networks, transformers, and distributed models with detailed explanations of the underlying math and code.

Use cases

• learn how neural networks work internally
• implement a neural network from scratch with numpy
• understand forward and backpropagation step by step
• build a transformer without frameworks
• study machine learning fundamentals with runnable notebooks
• see how weights, biases, and activation functions work

When to choose

• you want to deeply understand ML internals rather than use a high-level framework
• you prefer minimal dependencies like NumPy only
• you learn best from annotated, executable notebooks

When to avoid

• you need production-ready, optimized training code
• you want GPU acceleration or distributed training at scale
• you need a maintained library API rather than educational material

Facets

learning-resource · maturity active

machine-learning deep-learning nlp machine-learning deep-learning education tutorials python from-scratch numpy jupyter-notebooks neural-networks transformer educational

Member repositories

For agents

markdown · JSON · MCP: product_card(name="DorsaRoh/Machine-Learning")