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The Machine & Deep Learning Compendium

Covering approximately 500 topics, the ML & DL Compendium includes summaries, links, and articles across a wide array of subjects, including LLMs. These range from modern machine learning algorithms and deep learning techniques to specialized areas like NLP, audio processing, computer vision (classic and deep), time-series analysis, anomaly detection, and graphs. It also deep dives into strategic themes like data science management, team building, and practical essentials like product management, design, and technology stacks from a data science perspective.

The ML & DL Compendium is completely open and now lives on GitHub (please star it!). Driven by my belief in knowledge-sharing and education, this project will always remain not-for-profit and free.

{% embed url="https://github.com/orico/www.mlcompendium.com" %} The ML & DL Compendium Official GitHub repo {% endembed %}

The Machine & Deep Learning Compendium began as a personal project—a curated list of resources I maintained in a private Google document for my own learning. That document has now evolved into this new interface, and I’m excited to share it as an educational tool to help others learn and connect with the brilliant authors I’ve summarized, quoted, and referenced.

I envision it as a go-to resource for learners of all levels—whether you're an industry data scientist, an academic, or just starting out. It’s designed to save you countless hours of searching and filtering through content, providing a streamlined path to invaluable authors and resources you can further support.

Let’s work together to support the community, amplify the voices of authors, and democratize education! If you spot something that could be improved, feel free to contribute via GitHub or reach out to me directly.

{% embed url="https://towardsdatascience.com/the-last-machine-deep-learning-compendium-youll-ever-need-dc973643c4e1" %} The ML Compendium Article {% endembed %}

Many Thanks,
Dr. Ori Cohen

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