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Publicado por John Wiley & Sons Inc, New York, 2022
ISBN 10: 111976047X ISBN 13: 9781119760474
Idioma: Inglés
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Añadir al carritoHardcover. Condición: new. Hardcover. MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoTs potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store contextualized marketing, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Publicado por John Wiley & Sons Inc, New York, 2022
ISBN 10: 111976047X ISBN 13: 9781119760474
Idioma: Inglés
Librería: CitiRetail, Stevenage, Reino Unido
EUR 186,58
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Añadir al carritoHardcover. Condición: new. Hardcover. MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoTs potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store contextualized marketing, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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EUR 225,36
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Original o primera edición
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoBuch. Condición: Neu. Neuware - MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONSAs companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoT's potential and this book brings clarity to the issue.Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems.Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store 'contextualized marketing', and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains.
Publicado por John Wiley & Sons Inc, New York, 2022
ISBN 10: 111976047X ISBN 13: 9781119760474
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 292,32
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: new. Hardcover. MACHINE LEARNING PARADIGM FOR INTERNET OF THINGS APPLICATIONS As companies globally realize the revolutionary potential of the IoT, they have started finding a number of obstacles they need to address to leverage it efficiently. Many businesses and industries use machine learning to exploit the IoTs potential and this book brings clarity to the issue. Machine learning (ML) is the key tool for fast processing and decision-making applied to smart city applications and next-generation IoT devices, which require ML to satisfy their working objective. Machine learning has become a common subject to all people like engineers, doctors, pharmacy companies, and business people. The book addresses the problem and new algorithms, their accuracy, and their fitness ratio for existing real-time problems. Machine Learning Paradigm for Internet of Thing Applications provides the state-of-the-art applications of machine learning in an IoT environment. The most common use cases for machine learning and IoT data are predictive maintenance, followed by analyzing CCTV surveillance, smart home applications, smart-healthcare, in-store contextualized marketing, and intelligent transportation systems. Readers will gain an insight into the integration of machine learning with IoT in these various application domains. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.