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Deep Learning Genome Mapping (15 results)
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Condition: As New. Unread book in perfect condition.
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Condition: New.
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Condition: New.
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Deep Learning in Genome Mapping : Computation and Analysis
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New.
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Deep Learning in Genome Mapping : Computation and Analysis
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Condition: New.
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Deep Learning In Genome Mapping: Computation And Analysis
Language: English
Published by Taylor & Francis Ltd, 2026
ISBN 10: 1032833815 ISBN 13: 9781032833811
Hardcover. Condition: Brand New. 218 pages. 9.18x6.12x9.21 inches. In Stock.
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Deep Learning in Genome Mapping (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032833815 ISBN 13: 9781032833811
Hardcover. Condition: new. Hardcover. The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field. This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Deep Learning in Genome Mapping (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032833815 ISBN 13: 9781032833811
Hardcover. Condition: new. Hardcover. The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field. This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Deep Learning in Genome Mapping
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
£ 180.40
£ 5.02 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dr. Soumya Ranjan Nayak is an Assistant Professor at the School of Computer Engineering, KIIT University, Odisha, India. He holds a Ph.D. and M.Tech in Computer Science and Engineering under an MHRD fellowship and has over 150 publications, 16 boo.
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Deep Learning in Genome Mapping (Hardcover)
Language: English
Published by Taylor & Francis Ltd, London, 2026
ISBN 10: 1032833815 ISBN 13: 9781032833811
Hardcover. Condition: new. Hardcover. The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field. This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Buch. Condition: Neu. Deep Learning in Genome Mapping | Computation and Analysis | Soumya Ranjan Nayak (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781032833811 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.
