Skip to content
The Internet Compass

Encyclopedia of Data Science and Machine Learning

Machine Learning in the Real World

Stylianos Kampakis

Published January 20, 2023Read PDF ↗View on arXiv ↗

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

Thank you to arXiv for use of its open access interoperability.

View original source ↗Spot an error on this page? Let us know →

FAQ

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.