Da: Books Puddle, New York, NY, U.S.A.
EUR 42,93
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Aggiungi al carrelloCondizione: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.
Da: Majestic Books, Hounslow, Regno Unito
EUR 42,59
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 43,88
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Da: BargainBookStores, Grand Rapids, MI, U.S.A.
EUR 57,52
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Recurrent Neural Networks: From Simple to Gated Architectures 0.47. Book.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 59,63
Convertire valutaQuantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 60,22
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 59,00
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Da: California Books, Miami, FL, U.S.A.
EUR 67,47
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Da: California Books, Miami, FL, U.S.A.
EUR 72,95
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Aggiungi al carrelloCondizione: New.
Da: Chiron Media, Wallingford, Regno Unito
EUR 54,50
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Aggiungi al carrelloPF. Condizione: New.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,56
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Aggiungi al carrelloCondizione: New. In.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 61,56
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Aggiungi al carrelloCondizione: New. In.
Da: Russell Books, Victoria, BC, Canada
EUR 67,70
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Aggiungi al carrellopaperback. Condizione: New. 1st ed. 2022. Special order direct from the distributor.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 61,46
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 62,15
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Springer International Publishing, Springer International Publishing, 2023
ISBN 10: 3030899314 ISBN 13: 9783030899318
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 53,49
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized) backpropagation through time (BPTT). This author focuses on the basics and nuances of recurrent neural networks, providing technical and principled treatment of the subject, with a view toward using coding and deep learning computational frameworks, e.g., Python and Tensorflow-Keras. Recurrent neural networks are treated holistically from simple to gated architectures, adopting the technical machinery of adaptive non-convex optimization with dynamic constraints to leverage its systematic power in organizing the learning and training processes. This permits the flow of concepts and techniques that provide grounded support for design and training choices. The author's approach enables strategic co-trainingof output layers, using supervised learning, and hidden layers, using unsupervised learning, to generate more efficient internal representations and accuracy performance. As a result, readers will be enabled to create designs tailoring proficient procedures for recurrent neural networks in their targeted applications.
Da: Revaluation Books, Exeter, Regno Unito
EUR 77,95
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 141 pages. 9.25x6.10x0.75 inches. In Stock.
Editore: Springer International Publishing, 2022
ISBN 10: 3030899284 ISBN 13: 9783030899288
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 58,84
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook provides a compact but comprehensive treatment that provides analytical and design steps to recurrent neural networks from scratch. It provides a treatment of the general recurrent neural networks with principled methods for training that render the (generalized) backpropagation through time (BPTT). This author focuses on the basics and nuances of recurrent neural networks, providing technical and principled treatment of the subject, with a view toward using coding and deep learning computational frameworks, e.g., Python and Tensorflow-Keras. Recurrent neural networks are treated holistically from simple to gated architectures, adopting the technical machinery of adaptive non-convex optimization with dynamic constraints to leverage its systematic power in organizing the learning and training processes. This permits the flow of concepts and techniques that provide grounded support for design and training choices. The author's approach enables strategic co-trainingof output layers, using supervised learning, and hidden layers, using unsupervised learning, to generate more efficient internal representations and accuracy performance. As a result, readers will be enabled to create designs tailoring proficient procedures for recurrent neural networks in their targeted applications.
Da: Revaluation Books, Exeter, Regno Unito
EUR 60,56
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 141 pages. 9.25x6.10x0.59 inches. In Stock. This item is printed on demand.