Challenges in Deploying Machine Learning: a Survey of Case Studies
November 18, 2020 Β· The Cartographer Β· π ACM Computing Surveys
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"Title-pattern auto-detect: Challenges in Deploying Machine Learning: a Survey of Case Studies"
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Authors
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
arXiv ID
2011.09926
Category
cs.LG: Machine Learning
Citations
514
Venue
ACM Computing Surveys
Last Checked
1 day ago
Abstract
In recent years, machine learning has transitioned from a field of academic research interest to a field capable of solving real-world business problems. However, the deployment of machine learning models in production systems can present a number of issues and concerns. This survey reviews published reports of deploying machine learning solutions in a variety of use cases, industries and applications and extracts practical considerations corresponding to stages of the machine learning deployment workflow. By mapping found challenges to the steps of the machine learning deployment workflow we show that practitioners face issues at each stage of the deployment process. The goal of this paper is to lay out a research agenda to explore approaches addressing these challenges.
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