Integration of Internet of Things and Machine Learning: Design Models, Architectures and Application - Tapa dura
Sinopsis
The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.
Features:
- Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model training
- Offers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical background
- Showcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturing
- Covers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning models
The text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Mudassir Khan is currently working as an Assistant Professor, in the Department of Computer Science, at King Khalid University Abha, Saudi Arabia. He has more than 13 years of Teaching Experience at the King Khalid University of Saudi Arabia and has published more than 42 papers in International Journals, and conferences. His research interests include big data, the Internet of Things, deep learning, machine learning, fuzzy logic, image processing, cyber security, and cloud computing.
Shaik Karimullah is currently serving as an Assistant Professor, in the Department of Electronics and Communication Engineering, at Annamacharya University, Andhra Pradesh, India. He has published research papers in the field of VLSI, and image processing in journals and conferences. His research interests include VLSI, image processing, wireless communications, and embedded systems. Fahimuddin Shaik is working as an Associate Professor, in the Department of Electronics and Communication Engineering, at Annamacharya University, Andhra Pradesh, India. His areas of research interest include image processing, medical imaging, segmentation, biomedical imaging, digital image processing, and computer vision. He has published research papers in journals and conferences.
Suman Lata Tripathi is working as a Professor at Lovely Professional University with more than 22 years of experience in academics and research. She has published more than 125 research papers in journals, and conference proceedings. Her area of expertise includes microelectronics device modelling and characterization, low-power VLSI circuit design, VLSI design of testing, advanced FET design for the Internet of Things, embedded system design, reconfigurable architecture with FPGAs, and biomedical applications.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Integration of Internet of Things and Machine Learning : Design Models, Architectures and Application
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Integration of Internet of Things and Machine Learning (Hardcover)
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Taylor & Francis Ltd, London, 2026
ISBN 10: 104106294X
ISBN 13: 9781041062943
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.Features:Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model trainingOffers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical backgroundShowcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturingCovers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning modelsThe text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text outlines the integration of the Internet of Things and machine learning to drive technological advancements across various sectors. It further highlights common challenges and pitfalls encountered in the Internet of Things and machine learning projects. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781041062943
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Integration of Internet of Things and Machine Learning : Design Models, Architectures and Application
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Integration of Internet of Things and Machine Learning : Design Models, Architectures and Application
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Integration of Internet of Things and Machine Learning : Design Models, Architectures and Application
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Integration of Internet of Things and Machine Learning (Hardcover)
Publicado por
Taylor & Francis Ltd, London, 2026
ISBN 10: 104106294X
ISBN 13: 9781041062943
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Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. The book highlights the importance of using machine learning algorithms for smart intelligent devices, security and privacy issues of the Internet of Things.Features:Discusses comprehensively topics such as sensor data collection, data preprocessing, feature extraction, and model trainingOffers simplified explanations of algorithms like neural networks, decision trees, and clustering techniques, making them accessible to readers with limited technical backgroundShowcases practical insights by presenting real-world applications of the Internet of Things, and machine learning in domains such as smart homes, healthcare, transportation, and manufacturingCovers issues such as data quality, model overfitting, security vulnerabilities, and scalability. Includes tutorials on setting up Internet of Things devices, collecting and preprocessing data, and building machine learning modelsThe text is primarily written for senior undergraduates, graduate students, and academic researchers in electrical engineering, electronics and communications engineering, computer science and engineering, and information technology. The text outlines the integration of the Internet of Things and machine learning to drive technological advancements across various sectors. It further highlights common challenges and pitfalls encountered in the Internet of Things and machine learning projects. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781041062943
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Integration of Internet of Things and Machine Learning: Design Models, Architectures and Application
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Integration of Internet of Things and Machine Learning
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Integration of Internet of Things and Machine Learning: Design Models, Architectures and Application
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