Encyclopedia of Data Science and Machine Learning
Machine Learning in the Real World
Stylianos Kampakis
Abstract
Most data scientists and machine learning practitioners focus on algorithm development and implementation. However, the proper and successful application of data science in an organisation cannot be separated from business objectives and organisational dynamics. This way of thinking, however, can feel foreign to many data scientists who focus mostly on technical details. The goal of this article is to outline some of the considerations that a data scientist needs to take into account when implementing data science within an organisation. More specifically, this article discusses the topics of data strategy, data science processes, and some recent developments like MLOps.
Sourced from arXiv · Updated September 2, 2026
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Common questions
What is "Machine Learning in the Real World" about?
Most data scientists and machine learning practitioners focus on algorithm development and implementation. However, the proper and successful application of data science in an organisation cannot be separated from business objectives and organisational dynamics. This way of think
Who wrote this paper?
Stylianos Kampakis
Where can I read the full paper?
The full text is available as a PDF on arXiv (linked above), published January 20, 2023.
Does this paper have a DOI?
Yes: 10.4018/978-1-7998-9220-5.ch104.