Caterini Anthony (12 results)
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
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Language: English
Published by Springer 2018-04, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
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PF. Condition: New.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
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Condition: New. pp. 100 1st ed. 2018 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer International Publishing, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: moluna, Greven, Germanymoluna
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Language: English
Published by Springer-Verlag New York Inc, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 84 pages. 9.00x6.00x0.25 inches. In Stock.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Deep Neural Networks in a Mathematical Framework | Anthony L. Caterini (u. a.) | Taschenbuch | xiii | Englisch | 2018 | Springer | EAN 9783319753034 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: pre…igu.
Language: English
Published by Springer, Berlin, Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools to represent and describe neural networks, casting previous results in the field in a more natural light. In…particular, the authors derive gradient descent algorithms in a unified way for several neural network structures, including multilayer perceptrons, convolutional neural networks, deep autoencoders and recurrent neural networks. Furthermore, the authors developed framework is both more concise and mathematically intuitive than previous representations of neural networks.This SpringerBrief is one step towards unlocking the black box of Deep Learning. The authors believe that this framework will help catalyze further discoveries regarding the mathematical properties of neural networks.This SpringerBrief is accessible not only to researchers, professionals and students working and studying in the field of deep learning, but alsoto those outside of the neutral network community.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
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Paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Brook Bookstore On Demand, Napoli, NA, ItalyBrook Bookstore On Demand
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer, Berlin, Springer International Publishing, Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools to represent and describe neural networks, casting previous results in the field in a more na…tural light. In particular, the authors derive gradient descent algorithms in a unified way for several neural network structures, including multilayer perceptrons, convolutional neural networks, deep autoencoders and recurrent neural networks. Furthermore, the authors developed framework is both more concise and mathematically intuitive than previous representations of neural networks.This SpringerBrief is one step towards unlocking the black box of Deep Learning. The authors believe that this framework will help catalyze further discoveries regarding the mathematical properties of neural networks.This SpringerBrief is accessible not only to researchers, professionals and students working and studying in the field of deep learning, but alsoto those outside of the neutral network community. 84 pp. Englisch.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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£ 92.36
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Condition: New. Print on Demand pp. 100.
Language: English
Published by Springer, 2018
Series: Book 256 of 322 - SpringerBriefs in Computer Science
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Condition: New. PRINT ON DEMAND pp. 100.
