ATOM00blue/machine-learning-library

Key features

• 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

Use cases

• 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

Topics

FAQ

What is 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.

Is machine-learning-library free to use? What license does it have?

machine-learning-library is open source under the Other license. Check the license terms before using it in commercial products.

Is machine-learning-library still maintained?

Updated within 6 months. The last commit to machine-learning-library was on Aug 10, 2026.

What can I use machine-learning-library for?

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

Where can I get machine-learning-library?

The source code and installation instructions are on GitHub: https://github.com/ATOM00blue/machine-learning-library