Selected Topics in Clinical Oncology

Debois, J. M.

doi:10.1007/978-94-011-4100-0

Cited by 1 publication

(2 citation statements)

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“…Those methodologies have similar aims, namely to deliver production-ready software products. A concept called "DevOps" emerged in the years 2008/2009 and aims to reduce issues in software development [10], [11]. DevOps is more than a pure methodology and rather represents a paradigm addressing social and technical issues in organizations engaged in software development.…”

Section: Foundations Of Devopsmentioning

confidence: 99%

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Machine Learning Operations (MLOps): Overview, Definition, and Architecture

2023

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The final goal of all industrial machine learning (ML) projects is to develop ML products and rapidly bring them into production. However, it is highly challenging to automate and operationalize ML products and thus many ML endeavors fail to deliver on their expectations. The paradigm of Machine Learning Operations (MLOps) addresses this issue. MLOps includes several aspects, such as best practices, sets of concepts, and development culture. However, MLOps is still a vague term and its consequences for researchers and professionals are ambiguous. To address this gap, we conduct mixed-method research, including a literature review, a tool review, and expert interviews. As a result of these investigations, we contribute to the body of knowledge by providing an aggregated overview of the necessary principles, components, and roles, as well as the associated architecture and workflows. Furthermore, we provide a comprehensive definition of MLOps and highlight open challenges in the field. Finally, this work provides guidance for ML researchers and practitioners who want to automate and operate their ML products with a designated set of technologies.

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Section: Foundations Of Devopsmentioning

confidence: 99%

“…(8) First, the feature engineering pipeline connects to the raw data, which can be (for instance) streaming data, static batch data, or data from any cloud storage. (9) The data will be extracted from the data sources (10). The data preprocessing begins with data transformation and cleaning tasks.…”

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confidence: 99%