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The fusion of AI and IoT enables the systems to be predictive,
prescriptive, and autonomous, and this convergence has evolved the
nature of emerging applications from being assisted to augmented,
and ultimately to autonomous intelligence. This book discusses
algorithmic applications in the field of machine learning and IoT
with pertinent applications. It further discusses challenges and
future directions in the machine learning area and develops
understanding of its role in technology, in terms of IoT security
issues. Pertinent applications described include speech
recognition, medical diagnosis, optimizations, predictions, and
security aspects. Features: Focuses on algorithmic and practical
parts of the artificial intelligence approaches in IoT
applications. Discusses supervised and unsupervised machine
learning for IoT data and devices. Presents an overview of the
different algorithms related to Machine learning and IoT. Covers
practical case studies on industrial and smart home automation.
Includes implementation of AI from case studies in personal and
industrial IoT. This book aims at Researchers and Graduate students
in Computer Engineering, Networking Communications, Information
Science Engineering, and Electrical Engineering.
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