mirror of
https://github.com/harvard-edge/cs249r_book.git
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fa5923610a
Aligns the repository with GitHub community-standard recommendations and makes the project's policies discoverable from the root, where contributors and tooling actually look for them. - CONTRIBUTING.md (root): router to per-project guides plus universal policies (branch from dev, ./book/binder setup, no `git add .`). - CODE_OF_CONDUCT.md (root): canonical Contributor Covenant 2.1, lifted from book/docs/. The book/docs version becomes a thin pointer so we have a single source of truth. - SECURITY.md: private vulnerability reporting via GitHub Security Advisory + maintainer email, with explicit in-scope/out-of-scope boundaries (textbook typos are not security issues). - CITATION.cff: machine-readable mirror of CITATION.bib so GitHub's "Cite this repository" button works. - .github/dependabot.yml: weekly bumps against `dev` for every actual ecosystem in the repo (pip, npm, github-actions), grouped where it makes sense (Next/React together). - .github/ISSUE_TEMPLATE/config.yml: blank_issues_enabled=false to keep reports on-template; added security-advisory contact link.
49 lines
1.6 KiB
YAML
49 lines
1.6 KiB
YAML
cff-version: 1.2.0
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message: >-
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If you use MLSysBook in academic work, teaching materials, or derived
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software, please cite it using the metadata below.
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type: book
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title: "MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering"
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abstract: >-
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An open-source two-volume textbook on machine learning systems engineering,
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spanning foundations of single-machine ML systems through distributed
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production systems at scale. Companion projects include TinyTorch
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(educational ML framework), Co-Labs (interactive WASM labs), Hardware Kits
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(embedded ML boards), MLSys-im (systems simulator), MLPerf EDU (educational
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benchmark suite), and StaffML (interview question corpus).
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authors:
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- family-names: Reddi
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given-names: Vijay Janapa
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affiliation: Harvard University
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email: vj@eecs.harvard.edu
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repository-code: "https://github.com/harvard-edge/cs249r_book"
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url: "https://mlsysbook.ai"
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license: CC-BY-NC-SA-4.0
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keywords:
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- machine learning systems
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- ML systems engineering
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- distributed systems
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- MLOps
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- hardware acceleration
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- edge AI
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- tinyml
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- textbook
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- open educational resources
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preferred-citation:
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type: conference-paper
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title: "MLSysBook.AI: Principles and Practices of Machine Learning Systems Engineering"
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authors:
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- family-names: Reddi
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given-names: Vijay Janapa
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affiliation: Harvard University
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year: 2024
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collection-title: >-
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2024 International Conference on Hardware/Software Codesign and System
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Synthesis (CODES+ISSS)
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publisher:
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name: IEEE
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start: 41
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end: 42
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doi: "10.1109/CODES-ISSS60120.2024.00015"
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url: "https://mlsysbook.org"
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