ATOM00blue/machine-learning-library

Recursos principais

• 01Custom APRL classifier and regressor for numeric tabular data using only NumPy
• 02Distance-aware uncertainty estimates and missing-value handling in APRL
• 03923 Markdown documents covering ML papers, lectures and articles
• 04Every file includes YAML frontmatter with source, URL, authors and tags
• 05Organized into a 17-topic map with navigation hubs and reading paths
• 06Works as an Obsidian vault or with AI agents via bundled AGENTS.md and CLAUDE.md

Casos de uso

• Building a retrieval-based ML tutor that cites specific papers or lectures
• Studying machine learning from a single offline, searchable Markdown collection
• Experimenting with a small, inspectable classifier or regressor on tabular data
• Creating a domain text dataset for embedding benchmarks or model fine-tuning

Tópicos

Perguntas frequentes

O que é machine-learning-library?

A curated Markdown knowledge base of 923 ML papers, lectures and articles, plus a small NumPy-only custom classifier and regressor called APRL.

machine-learning-library é gratuito? Qual é a licença?

machine-learning-library é open source sob a licença Other. Confira os termos da licença antes de usá-lo em produtos comerciais.

machine-learning-library ainda é mantido?

Atualizado nos últimos 6 meses. O último commit de machine-learning-library foi em 10 de ago. de 2026.

Para que posso usar machine-learning-library?

Building a retrieval-based ML tutor that cites specific papers or lectures Studying machine learning from a single offline, searchable Markdown collection Experimenting with a small, inspectable classifier or regressor on tabular data Creating a domain text dataset for embedding benchmarks or model fine-tuning

Onde consigo machine-learning-library?

O código-fonte e as instruções de instalação estão no GitHub: https://github.com/ATOM00blue/machine-learning-library