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A hand-curated, topic-organized library of the best ML education — 923 docs (391 arXiv papers, 474 Stanford/MIT/Karpathy/fast.ai lectures, 58 explainer articles), normalized to Markdown with full provenance. Open it in Obsidian or point your agent at it. A clean ML corpus for learning, RAG & fine-tuning.
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Written in Python, licensed under Custom.
It has been tracked on GitGem.org since June 2, 2026. It has 125 stars and 13 forks, with its most recent commit about a month ago.
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May 29
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