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MLOps -- Definitions, Tools and Challenges

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arxiv 2201.00162 v1 pith:R4AEIKIZ submitted 2022-01-01 cs.LG cs.SE

G. Symeonidis , E. Nerantzis , A. Kazakis , G.A. Papakostas This is my paper · ORCID
classification cs.LGcs.SE
keywords mlopslearningmachinetoolsareaautomatedautomlchallenges
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to define the operation and the components of such systems by highlighting the current problems and trends. In this context, we present the different tools and their usefulness in order to provide the corresponding guidelines. Moreover, the connection between MLOps and AutoML (Automated Machine Learning) is identified and how this combination could work is proposed.

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  1. Maturity Framework for Enhancing Machine Learning Quality

    cs.LG 2025-02 conditional novelty 4.0 of 10

    A quality score and five-level maturity framework for ML systems, open-sourced and rolled out at Booking.com to track and improve ML quality.

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