Deep Learning in Genome Mapping: Computation and Analysis

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Bol 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. 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.

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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. 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.

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Pagina's: 212, Editie: Eerste editie, Hardcover, CRC Press


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  • 9781032833811
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