License
LICENSE
Open by design.
The curriculum is free to read, teach from, and adapt, and it always will be.
The textbook is published by MIT Press under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). The teaching materials around it (labs, kits, slides, and the Instructor Hub) use the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), and the software components carry their own licenses, listed below.
By component
Textbook
CC BY-NC-ND 4.0
The license of the MIT Press edition. Free to read and share for non-commercial use with credit; modified versions, including translations, need permission.
Labs, Kits, Slides, Instructor Hub
CC BY-NC-SA 4.0
Free to share and adapt for non-commercial use. Must give credit and share under the same license.
TinyTorch
MIT
Permissive open-source license. Use it, modify it, build on it, including in commercial projects.
MLSys·im
Apache 2.0
The Python infrastructure-modeling package is permissively licensed for research, teaching, and commercial use.
StaffML
CC BY-NC 4.0 for the question corpus
AGPL v3 for the web app
The questions may be shared and adapted with credit for non-commercial use. The app is open source with copyleft.
For educators
You are welcome to teach from the textbook in your courses, in part or in whole, and to share it with your students. The slides, labs, and other teaching materials may also be adapted to your syllabus. Translations or other modified versions of the textbook text need permission. All we ask is that you credit the source and share your improvements to the teaching materials with the community.
For institutions
If you are considering adopting this curriculum at your university or organization and have questions about licensing, please reach out to edu@tinyML.org.
Citation
If you use this work in academic research, please cite:
title={Introduction to Machine Learning Systems},
author={Reddi, Vijay Janapa},
publisher={MIT Press},
year={2026},
isbn={978-0-262-05888-9},
url={../vol1/}
}
@book{reddi2027mlsys,
title={Scaling Machine Learning Systems},
author={Reddi, Vijay Janapa},
publisher={MIT Press},
year={2027},
url={../vol2/}
}
@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},
publisher={IEEE},
doi={10.1109/CODES-ISSS60120.2024.00015}
}