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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Language: English
Published by Elsevier Science Publishing Co Inc, 2019
ISBN 10: 0128167181 ISBN 13: 9780128167182
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 182.09
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Condition: As New. Unread book in perfect condition.
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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Taschenbuch. Condition: Neu. Deep Learning and Parallel Computing Environment for Bioengineering Systems | Arun Kumar Sangaiah | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2019 | Elsevier Inc | EAN 9780128167182 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketCondition: New. Presents novel, in-depth research contributions from a methodological/application perspective in understanding the fusion of deep machine learning paradigms and their capabilities in solving a diverse range of problems Illustrates the stat.
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Condition: new. Questo è un articolo print on demand.
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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Language: English
Published by Elsevier Science & Technology, Academic Press, 2019
ISBN 10: 0128167181 ISBN 13: 9780128167182
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas. Englisch.
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Add to basketPaperback. Condition: Brand New. 320 pages. 11.00x8.50x1.25 inches. In Stock. This item is printed on demand.
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Deep Learning and Parallel Computing Environment for Bioengineering Systems
Language: English
Published by Elsevier Science & Technology, Academic Press, 2019
ISBN 10: 0128167181 ISBN 13: 9780128167182
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing the gathered knowledge and applying it to multiple domains including health care, social networks, mining, recommendation systems, image processing, pattern recognition and predictions using deep learning paradigms is the major strength of this book. This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians. The proposed techniques and concepts in this book can be extended in future to accommodate changing business organizations' needs as well as practitioners' innovative ideas.
