Description: Big Data Analytics for Cyber-Physical Systems : Machine Learning for the Internet of Things, Paperback by Dartmann, Guido (EDT); Song, Houbing (EDT); Schmeink, Anke (EDT), ISBN 0128166371, ISBN-13 9780128166376, Like New Used, Free shipping in the US Big Data Analytics in Cyber-Physical Systems: Machine Learning for the Internet of Things examines sensor signal processing, IoT gateways, optimization and decision-making, intelligent mobility, and implementation of machine learning algorithms in embedded systems. This book focuses on the interaction between IoT technology and the mathematical tools used to evaluate the extracted data of those systems. Each chapter provides the reader with a broad list of data analytics and machine learning methods for multiple IoT applications. Additionally, this volume addresses the educational transfer needed to incorporate these technologies into our society by examining new platforms for IoT in schools, new courses and concepts for universities and adult education on IoT and data science. Bridges the gap between IoT, CPS, and mathematical modelling Features numerous use cases that discuss how concepts are applied in different domains and applications Provides "best practices", "winning stories" and "real-world examples" to complement innovation Includes highlights of mathematical foundations of signal processing and machine learning in CPS and IoT
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Book Title: Big Data Analytics for Cyber-Physical Systems : Machine Learning
Number of Pages: 396 Pages
Language: English
Publication Name: Big Data Analytics for Cyber-Physical Systems : Machine Learning for the Internet of Things
Publisher: Elsevier
Subject: Data Modeling & Design, Transportation, General
Publication Year: 2019
Type: Textbook
Subject Area: Law, Computers
Item Length: 9 in
Author: Houbing Herbert Song
Item Width: 6 in
Format: Trade Paperback
