afshinea/stanford-cs-229-machine-learning

Covers supervised, unsupervised, and deep learning algorithms alongside foundational refreshers in probability, statistics, algebra, and calculus. Content is organized modularly—individual cheatsheets for each ML subfield plus a unified "super cheatsheet"—and available in 10+ languages across PDF and web formats. Designed as a comprehensive reference guide integrating course prerequisites with practical training tips for practitioners.

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