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Machine Learning Applications Emerging (73 results)
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Machine Learning Applications: Emerging Trends (De Gruyter Frontiers in Computational Intelligence, 5)
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Machine Learning Applications: Emerging Trends
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Enabling Machine Learning Applications in Data Science. Proceedings of Arab Conference for Emerging Technologies 2020.
Published by Singapore, Springer., 2021
ISBN 10: 981336128X ISBN 13: 9789813361287
Language: English
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Add to basketXII, 404 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Algorithms for Intelligent Systems. Sprache: Englisch.
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
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Domain-Specific Computer Architectures for Emerging Applications : Machine Learning and Neural Networks
Published by Chapman and Hall/CRC, 2024
ISBN 10: 0367374536 ISBN 13: 9780367374532
Language: English
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Machine Learning - Advanced Techniques and Emerging Applications
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Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics: Theories and Applications
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Machine Learning Applications: Emerging Trends (De Gruyter Frontiers in Computational Intelligence, 5)
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Domain-Specific Computer Architectures for Emerging Applications : Machine Learning and Neural Networks
Published by Chapman and Hall/CRC, 2024
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Language: English
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Domain-Specific Computer Architectures for Emerging Applications : Machine Learning and Neural Networks
Published by Chapman and Hall/CRC, 2024
ISBN 10: 0367374536 ISBN 13: 9780367374532
Language: English
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Domain-Specific Computer Architectures for Emerging Applications: Machine Learning and Neural Networks
Published by Taylor & Francis Ltd, 2024
ISBN 10: 0367374536 ISBN 13: 9780367374532
Language: English
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Domain-Specific Computer Architectures for Emerging Applications : Machine Learning and Neural Networks
Published by Chapman and Hall/CRC, 2024
ISBN 10: 0367374536 ISBN 13: 9780367374532
Language: English
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Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering (Emerging Trends in Biomedical Technologies and Health informatics)
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Condition: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
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US$ 144.99
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
