Challenges in Deploying Machine Learning: A Survey of Case Studies

Author:

Paleyes Andrei1ORCID,Urma Raoul-Gabriel2ORCID,Lawrence Neil D.1ORCID

Affiliation:

1. University of Cambridge, Cambridge, United Kingdom

2. Cambridge Spark, Cambridge, United Kingdom

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 article is to lay out a research agenda to explore approaches addressing these challenges.

Funder

Alan Turing Institute

UK Research & Innovation

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

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