#538 · Primary category: Education & Research

www.mlcompendium.com

algorithms data-science deep-learning full-stack gitbook machine-learning marketing mlcompendium probability product-management statistics ux-design ux-experience ux-research

The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing project compiled using Gitbook.

Project last updated:06/19/25

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Why we included this project

This compendium started as one practitioner's private study notes and grew into an open, free Gitbook with around 500 topics. Each topic comes as a short summary plus links to the original authors and deeper reading, covering classic algorithms, LLMs, computer vision, audio, time series, graphs, and anomaly detection. What makes it useful beyond the technical side is that it also pulls together material on managing data science teams, product thinking, and choosing a technology stack, which most learning references skip. It is an educational resource to browse, not deployable software, so think of it as a well-curated companion for anyone from newcomers to working data scientists.

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