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Автор: Wolfgang Pietsch
Издательство: Springer
Год: 2022
Страниц: 308
Язык: английский
Формат: pdf (true)
Размер: 10.0 MB
This book addresses controversies concerning the epistemological foundations of Data Science: Is it a genuine science? Or is Data Science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of Data Science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in Data Science. Introductions to algorithms and brief case studies of successful Data Science such as machine translation are included. Data Science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in Data Science.