MACHINE LEARNING SYSTEMS

Principles and Practices of Engineering Artificially Intelligent Systems

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Our mission: To make AI systems education globally accessible — one learner, one lab, and one system at a time.

📘 This repo contains the source for the open textbook Machine Learning Systems: Principles and Practices of Engineering Artificially Intelligent Systems.

🔗 For the full learning experience — textbook, hands-on labs, educational frameworks, kits, and community — visit:
👉 https://mlsysbook.org

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📚 Read the Book

• 📖 Read online — continuously updated version
• 📄 Download PDF — for offline access

Core Topics:

• ML system design & modularity
• Data collection & labeling pipelines
• Model architecture & optimization
• Deployment, MLOps & monitoring
• Edge AI & resource-constrained platforms

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🧠 About the Project

MLSysBook began as a Harvard course and has since grown into a global educational movement focused on teaching ML through a systems-first lens.

We go beyond training models — our goal is to help learners understand and build the full stack of real-world ML systems, from edge devices to cloud-scale deployment.

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🚀 Contribute

We welcome contributions from around the world — from students, educators, researchers, and practitioners.

Ways to contribute:

• Suggest edits or improvements
• Add examples or diagrams
• Translate or adapt content for local needs
• Build companion tools or extensions

🛠️ A detailed contribution guide is coming soon!

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🔧 Build the Book Locally

To build and preview the book using Quarto:

1. Install Quarto

2. Clone the repo:

   git clone https://github.com/MLSysBook/mlsysbook.git
   cd mlsysbook

3. Render the book:

   quarto render

4. Open _book/index.html in your browser.

See BUILD.md for full instructions.

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📖 Citation

@inproceedings{reddi2024mlsysbook,
  title        = {MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering},
  author       = {Reddi, Vijay Janapa},
  booktitle    = {2024 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ ISSS)},
  pages        = {41--42},
  year         = {2024},
  organization = {IEEE},
  url          = {https://mlsysbook.org},
  note         = {Available at: https://mlsysbook.org}
}

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🛡️ License

This work is licensed under a Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International License (CC BY-NC-SA 4.0)

You may share and adapt the material for non-commercial purposes, with appropriate credit and under the same license.

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💡 Learn More

• 🌐 mlsysbook.org — main site and learning platform
• 🔥 TinyTorch — educational ML framework
• 💸 Open Collective — support this initiative
• 🧠 GitHub Discussions — ask questions or share insights

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Join us in making systems-level ML education open, practical, and global.