Guide to Deep Learning Basics Logical, Historical and Philosophical
This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cogn
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Guide to Deep Learning Basics Logical, Historical and Philosophical Perspectives
Guide to Deep Learning Basics
Sandro Skansi Editor
Guide to Deep Learning Basics Logical, Historical and Philosophical Perspectives
123
Editor Sandro Skansi Faculty of Croatian Studies University of Zagreb Zagreb, Croatia
ISBN 978-3-030-37590-4 ISBN 978-3-030-37591-1 https://doi.org/10.1007/978-3-030-37591-1
(eBook)
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Preface
Artificial neural networks came to existence in 1943 with the seminal paper by Walter Pitts and Warren McCulloch. It is commonly said that the rest is history. But this history, which is seldom explored, holds many interesting details. From the purely historical unknowns to the conceptual connections often spanning back to medieval and even classical times which we often take for granted. By doing so, we often simplify things to a degree when it is no longer evident how rich and intricate the history (and prehistory) of deep learning was. The present volume brings new light on some foundational issues, and we hope that it will shed a new light on this amazing field of research. My personal pivotal point for editing this volume was the discovery of a lost Croatian machine translation project from 1959. It was interesting to see how I was rediscovering the ideas that were so geographically close, and yet so remote and lost. But one question arose: If there was a whole project in machine translation no one knows about, what else is there to dig out? Can we find new old ideas that contribute to the rich history deep learning? Or more generally, how did this amazing field survive against the tide and finally fl
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