Neu Erschienen: 14.02.2020 Abbildung von Calin | Deep Learning Architectures | 1st ed. 2020 | 2020 | A Mathematical Approach

Calin

Deep Learning Architectures

A Mathematical Approach

lieferbar ca. 10 Tage als Sonderdruck ohne Rückgaberecht

auch verfügbar als eBook (PDF) für 90.94 €

1st ed. 2020 2020. Buch. xxx, 760 S. 178 s/w-Abbildungen, 35 Farbabbildungen, Bibliographien. Hardcover

Springer. ISBN 978-3-030-36720-6

Format (B x L): 15,5 x 23,5 cm

Gewicht: 1712 g

In englischer Sprache

Das Werk ist Teil der Reihe: Springer Series in the Data Sciences

Produktbeschreibung

This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.

Autoren

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