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Machine Learning in the Real World
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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.
IGI Global Scientific Publishing
Title: Machine Learning in the Real World
Description:
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.
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