Introduction to Machine Learning Systems
MACHINE LEARNING SYSTEMS
Principles and Practices of Engineering Artificially Intelligent Systems
🚀 Our Mission
1 GitHub ⭐ = 1 Learner 👩🎓
Every GitHub ⭐ tells a unique story: Learners acquiring knowledge and skills, and supporters encouraging us to push forward. Together, we are all collectively shaping the future of AI education at a global scale.
🌟 How Your Stars Make an Impact
Thanks to your support, we’re driving meaningful change in AI education.
Organizations such as Arduino and SEEED Studio are partnering with us to deliver AI hardware kits to underserved learners around the world, enabling them to explore cutting-edge technologies.
In addition, for every new GitHub ⭐, the EDGE AI Foundation is matching academic scholarship funds, empowering even more learners to access AI education.
⭐ So... Please Keep the Momentum Going - Star Our Repo! ⭐
📰 Latest Updates
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🎓 [Nov 15] Matching Academic Scholarship Funds
The EDGE AI Foundation is matching scholarship funds for every new GitHub ⭐ (up to 10,000 stars). Click here to show support! -
⭐ [Oct 18] We Hit 1,000 GitHub Stars! 🎉
Thanks to you, Arduino and SEEED donated AI hardware kits for TinyML workshops in developing nations!
📚 Explore the Book
- Read Online: View the most recent and fully rendered version of the book on our website.
- Download PDF: Get a downloadable PDF version of the entire book for offline reading.
🤝 Contributing
We believe that the best learning and development happen when people come together to share knowledge and ideas. Whether you’re a seasoned expert or just starting your journey in machine learning, your contributions can be valuable to share with the community.
Why Contribute?
- Share Your Expertise: If you have experience or insights in a specific area of machine learning or TinyML, your contributions can help others learn and apply these concepts.
- Learn and Grow: Contributing to this project is a great way to deepen your understanding of machine learning systems. As you write, code, or review content, you’ll reinforce your own knowledge and discover new aspects of the field.
- Collaborate and Network: Join a community of like-minded individuals passionate about advancing AI education. Collaborate with peers, receive feedback, and make connections that could lead to exciting opportunities.
- Make an Impact: Your contributions can directly influence how others understand and engage with machine learning. By improving and expanding the content, you’re helping shape the education of future engineers and AI practitioners.
How to Get Started
Getting started is easy! Whether you’re interested in writing a new chapter, fixing a bug, or suggesting an improvement, we welcome all forms of contribution. Here’s how you can begin:
- Explore the Repository: Familiarize yourself with the structure and content of the book by browsing the repository.
- Check Out the Guidelines: Review our contribution guidelines to understand how to contribute effectively.
- Choose Your Area: Pick a topic or area you’re passionate about. It could be anything from writing a new section, improving existing content, or even helping with code snippets and examples.
- Submit Your Contribution: Once you’re ready, submit a pull request. We review all contributions and provide feedback to help you refine your work.
Need Help?
If you’re unsure where to start or have any questions, feel free to reach out through our GitHub Discussions or open an issue. We’re here to support you throughout the process!
🚀 Want to Build the Book Locally?
If you’d like to build the book locally, follow these steps:
- Install Quarto: Follow the Quarto installation instructions.
- Render the Book in all formats:
cd cs249r_book quarto render - Render the Book in a specific format (works faster):
cd cs249r_book quarto render --to epub
For a complete setup guide, including dependency installation, see BUILD.md.
Contributors
This project follows the all-contributors specification. Contributions of any kind are welcome!
