integration internet things machine (16 résultats)

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Etat : New.

Etat : New.

Etat : New.

Hardcover. Etat : Brand New. 400 pages. 9.18x6.12x9.21 inches. In Stock.

Hardcover. Etat : 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.

Hardcover. Etat : 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.

HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 publ.

Buch. Etat : Neu. Integration of Internet of Things and Machine Learning | Design Models, Architectures and Application | Mudassir Khan (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781041062943 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Etat : 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.