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cff-version: 1.2.0
message: >-
If you use MLSysBook in academic work, teaching materials, or derived
software, please cite it using the metadata below.
type: book
title: "MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering"
abstract: >-
An open-source two-volume textbook on machine learning systems engineering,
spanning foundations of single-machine ML systems through distributed
production systems at scale. Companion projects include TinyTorch
(educational ML framework), Co-Labs (interactive WASM labs), Hardware Kits
(embedded ML boards), MLSys-im (systems simulator), MLPerf EDU (educational
benchmark suite), and StaffML (interview question corpus).
authors:
- family-names: Reddi
given-names: Vijay Janapa
affiliation: Harvard University
email: vj@eecs.harvard.edu
repository-code: "https://github.com/harvard-edge/cs249r_book"
url: "https://mlsysbook.ai"
license: CC-BY-NC-SA-4.0
keywords:
- machine learning systems
- ML systems engineering
- distributed systems
- MLOps
- hardware acceleration
- edge AI
- tinyml
- textbook
- open educational resources
preferred-citation:
type: conference-paper
title: "MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering"
authors:
- family-names: Reddi
given-names: Vijay Janapa
affiliation: Harvard University
year: 2024
collection-title: >-
2024 International Conference on Hardware/Software Codesign and System
Synthesis (CODES+ISSS)
publisher:
name: IEEE
start: 41
end: 42
doi: "10.1109/CODES-ISSS60120.2024.00015"
url: "https://mlsysbook.org"