Machine Learning in Cognitive IoT

This book covers the different technologies of Internet, and machine learning (ML) capabilities involved in Cognitive Internet of Things (CIoT). ML is explored by covering all the technical issues and various models used for data analytics during decision making at different steps. It initiates with IoT basics, its history, architecture and applications followed by capabilities of CIoT in real world and description of ML in data mining. Further, it explains various ML techniques and paradigms with different phases of data pre-processing and feature engineering. Each chapter includes sample questions to help understand concepts of ML used in different applications. Aimed at researchers, professionals and graduate students in computer science and engineering, computer applications and electronics engineering, wireless communications and networking, this book Explains integration of machine learning in IoT for building an efficient decision support system Covers IoT, CIoT, machine learning paradigms and models Includes implementation of machine learning models in R Help the analysts and developers to work efficiently with emerging technologies such as data analytics, data processing, big data, and robotics Includes programming codes in Python/MATLAB/R along with practical examples, questions, and multiple-choice questions