MLOps: A Taxonomy and a Methodology-Reference-Cited by-同舟云学术

MLOps: A Taxonomy and a Methodology

Author:

Testi Matteo¹^ORCID,Ballabio Matteo²^ORCID,Frontoni Emanuele³,Iannello Giulio⁴^ORCID,Moccia Sara⁵,Soda Paolo⁴^ORCID,Vessio Gennaro⁶^ORCID

Affiliation:

1. Integrated Research Centre, Università Campus Bio-Medico di Roma, Rome, Italy

2. DeepLearningItalia, Bergamo, Italy

3. Department of Political Sciences, Communication and International Relations, VRAI Laboratory, Università degli Studi di Macerata, Macerata, Italy

4. Department of Engineering, Unit of Computer Systems and Bioinformatics, Università Campus Bio-Medico di Roma, Rome, Italy

5. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy

6. Department of Computer Science, Università degli Studi di Bari Aldo Moro, Bari, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference98 articles.

3. Hidden technical debt in machine learning systems;sculley;Proc Adv Neural Inf Process Syst,2015

5. Engineering framework for scalable machine learning operations;scotton,2021

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