Principles and Practices of Engineering Artificially Intelligent Systems
The open-source textbook that teaches you to build real-world AI systems — from edge devices to cloud deployment. Originally developed as Harvard University's CS249r course by Prof. Vijay Janapa Reddi, now used by universities and students worldwide.
Our mission: Expand access to AI systems education worldwide — empowering learners, one chapter and one lab at a time.
"This grew out of a concern that while students could train AI models, few understood how to build the systems that actually make them work. As AI becomes more capable and autonomous, the critical bottleneck won't be the algorithms - it will be the engineers who can build efficient, scalable, and sustainable systems that safely harness that intelligence."
— Vijay Janapa Reddi
Go beyond training models — master the full stack of real-world ML systems.
| Topic | What You'll Build |
|---|---|
| System Design | Scalable, maintainable ML architectures |
| Data Engineering | Robust pipelines for collection, labeling, and processing |
| Model Deployment | Production-ready systems from prototypes |
| MLOps & Monitoring | Reliable, continuously operating systems |
| Edge AI | Resource-efficient deployment on mobile, embedded, and IoT |
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| Resource | Description |
|---|---|
| 📚 Main Site | Complete learning platform |
| 🔥 TinyTorch | Educational ML framework |
| 💬 Discussions | Ask questions, share insights |
| 👥 Community | Join our global learning community |
# Read online (continuously updated)
open https://mlsysbook.ai
# Or download PDF for offline access
curl -O https://mlsysbook.ai/Machine-Learning-Systems.pdfgit clone https://github.com/harvard-edge/cs249r_book.git
cd cs249r_book
make setup-hooks # Setup automated quality controls
make install # Install dependencies
make preview # Start development serverWe welcome contributions from the global community! Here's how you can help:
- 📝 Content — Suggest edits, improvements, or new examples
- 🛠️ Tools — Enhance development scripts and automation
- 🎨 Design — Improve figures, diagrams, and visual elements
- 🌍 Localization — Translate content for global accessibility
- 🔧 Infrastructure — Help with build systems and deployment
All contributions benefit from automated quality assurance:
- ✅ Pre-commit validation — Automatic cleanup and checks
- 📋 Content review — Formatting and style validation
- 🧪 Testing — Build and link verification
- 👥 Peer review — Community feedback
# Building
make build # Build HTML version
make build-pdf # Build PDF version
make preview # Start development server
# Quality Control
make clean # Clean build artifacts
make test # Run validation tests
make lint # Check for issues
# Get help
make help # Show all commandsMLSysBook/
├── book/ # Main book content (Quarto)
│ ├── contents/ # Chapter content
│ │ ├── core/ # Core chapters
│ │ ├── labs/ # Hands-on labs
│ │ ├── frontmatter/ # Preface, acknowledgments
│ │ └── parts/ # Book parts and sections
│ ├── _quarto.yml # Book configuration
│ ├── index.qmd # Main entry point
│ └── assets/ # Images, styles, media
├── build/ # Build artifacts (git-ignored)
│ ├── html/ # HTML website output
│ ├── pdf/ # PDF book output
│ └── dist/ # Distribution files
├── tools/ # Development automation
│ ├── scripts/ # Organized development scripts
│ │ ├── build/ # Build and development tools
│ │ ├── content/ # Content management tools
│ │ ├── maintenance/ # System maintenance scripts
│ │ ├── testing/ # Test and validation scripts
│ │ ├── utilities/ # General utility scripts
│ │ └── docs/ # Script documentation
│ ├── dependencies/ # Package requirements
│ └── setup/ # Setup and configuration
├── config/ # Build configuration
│ ├── _extensions/ # Quarto extensions
│ ├── lua/ # Lua scripts
│ └── tex/ # LaTeX templates
├── assets/ # Global assets (covers, icons)
├── docs/ # Documentation
│ ├── DEVELOPMENT.md # Development guide
│ ├── MAINTENANCE_GUIDE.md # Daily workflow guide
│ ├── BUILD.md # Build instructions
│ └── contribute.md # Contribution guidelines
└── Makefile # Development commands
- 📋 Development Guide — Comprehensive setup and workflow
- 🛠️ Maintenance Guide — Daily tasks and troubleshooting
- 🔨 Build Instructions — Detailed build process
- 🤝 Contribution Guidelines — How to contribute effectively
@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}
}This work is licensed under Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International (CC BY-NC-SA 4.0). You may share and adapt the material for non-commercial purposes with appropriate credit.
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Empowering the next generation of AI systems engineers
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