Vol. 1 No. 2 (2021): High Value Added, Resilient and Sustainable Industry
Articles

Data and Machine Learning in Decision-making

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  • Pedro Amorim,
  • José Fernando Oliveira
Pedro Amorim
INESC TEC, Faculty of Engineering of the University of Porto
José Fernando Oliveira
INESC TEC, Faculty of Engineering of the University of Porto

Published 2021-06-14

How to Cite

Amorim, P., & Fernando Oliveira, J. (2021). Data and Machine Learning in Decision-making. INESC TEC Science&Society, 1(2). Retrieved from https://science-society.inesctec.pt/index.php/inesctecesociedade/article/view/50

Copyright (c) 2021 INESC TEC Science&Society

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

All models are incomplete and approximate. Modelling is extracting from a reality that is always chaotic and complex, the essential characteristics for the decision-making process in question, organizing, simplifying, and creating meaning and purpose. This is only possible at the cost of a high dose of abstraction and simplification.

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