This repository archives notes, slides, and video links from San Diego Machine Learning (SDML) book club meetings. It serves as a central resource for individuals interested in self-study and discussion of various machine learning and related topics, providing curated materials for structured learning.

How It Works

The repository organizes content by book or topic, with each section linking to specific Markdown files containing meeting schedules, notes, slides, and video recordings. This structure facilitates easy navigation and access to materials for past and ongoing study groups, enabling members to follow along or catch up on discussions.

Quick Start & Requirements

• Access to the repository content via GitHub.
• No specific installation or runtime requirements beyond a web browser.
• Links to external resources like Coursera, YouTube, and other GitHub repositories are provided for specific topics.

Highlighted Details

• Comprehensive coverage of popular ML books including "Mathematics for Machine Learning," "Understanding Deep Learning," and "Hands-On Machine Learning."
• Dedicated sections for emerging fields like Generative AI, Probabilistic Machine Learning, and Quantum Computing.
• Links to Jupyter notebooks for hands-on coding examples from select books.

Maintenance & Community

• Managed by SanDiegoMachineLearning.
• Community engagement encouraged via their Meetup group and Slack channel.

Licensing & Compatibility

• Content is generally available for viewing and learning. Specific licensing for shared code or slides would depend on the original creators' terms.

Limitations & Caveats

This repository is an archive of past events and does not provide interactive learning tools or direct support for the covered topics. Users must access external platforms for course materials or code execution.