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Automated Machine Learning for Business$
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Kai R. Larsen and Daniel S. Becker

Print publication date: 2021

Print ISBN-13: 9780190941659

Published to Oxford Scholarship Online: July 2021

DOI: 10.1093/oso/9780190941659.001.0001

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Implement, Document, and Maintain

Implement, Document, and Maintain

(p.219) Section VI Implement, Document, and Maintain
Automated Machine Learning for Business

Kai R. Larsen

Daniel S. Becker

Oxford University Press

This section covers the final section of the machine learning life cycle. Consider these the most important steps of the entire process. This is the point at which we have the greatest potential to help our organization reap the benefits of machine learning. In traditional information systems development, 60–80% of the cost of a system comes during the maintenance phase, so these steps are important. This section covers how to deploy a machine learning model, as well as documenting and maintaining this model. A chapter covers the seven types of target leakage followed by time-aware validation and time-series analysis.

Keywords:   prediction system implementation, deployment strategies, Application Programming Interface (API), model documentation, model monitoring, model maintenance, target leakage, time-aware analysis, time-series analysis, DataRobot

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