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Verlag: O'Reilly Media (edition 1), 2023
ISBN 10: 1098102436 ISBN 13: 9781098102432
Sprache: Englisch
Anbieter: BooksRun, Philadelphia, PA, USA
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In den WarenkorbPaperback. Zustand: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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Verlag: The Institution of Engineering and Technology, 2021
ISBN 10: 1839533234 ISBN 13: 9781839533235
Sprache: Englisch
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Verlag: Springer International Publishing, 2022
ISBN 10: 3030719774 ISBN 13: 9783030719777
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 160,49
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic,and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learninghaveproved its vast range of significance and,provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D.students, postdocs, and anyone interested in the subjects discussed.
Verlag: Springer International Publishing, 2021
ISBN 10: 303071974X ISBN 13: 9783030719746
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 160,49
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic,and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learninghaveproved its vast range of significance and,provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D.students, postdocs, and anyone interested in the subjects discussed.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
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Verlag: Springer Nature Singapore, Springer Nature Singapore, 2025
ISBN 10: 9819993814 ISBN 13: 9789819993819
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 175,09
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.
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