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Data Analysis: Models or Techniques? [Book Review]
Foundations of Science 18 (3):579-581 (2013)
Abstract
In this commentary to Napoletani et al. (Found Sci 16:1–20, 2011), we argue that the approach the authors adopt suggests that neural nets are mathematical techniques rather than models of cognitive processing, that the general approach dates as far back as Ptolemy, and that applied mathematics is more than simply applying results from pure mathematicsAuthor's Profile
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Citations of this work
Two Dimensions of Opacity and the Deep Learning Predicament.Florian J. Boge - 2021 - Minds and Machines 32 (1):43-75.
Computer Simulations, Machine Learning and the Laplacean Demon: Opacity in the Case of High Energy Physics.Florian J. Boge & Paul Grünke - forthcoming - In Andreas Kaminski, Michael Resch & Petra Gehring (eds.), The Science and Art of Simulation II.
Processes Rather than Descriptions?Domenico Napoletani, Marco Panza & Daniele C. Struppa - 2013 - Foundations of Science 18 (3):587-590.
Artificial Diamonds are Still Diamonds.Domenico Napoletani, Marco Panza & Daniele C. Struppa - 2013 - Foundations of Science 18 (3):591-594.
References found in this work
Extending Ourselves: Computational Science, Empiricism, and Scientific Method.Paul Humphreys - 2004 - New York, US: Oxford University Press.
Agnostic Science. Towards a Philosophy of Data Analysis.D. C. Struppa - 2011 - Foundations of Science 16 (1):1-20.
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