This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIo T). Machine learning is explored by covering all the technical issues and various models used for data analytics during decision making at different steps. It initiates with Io T basics, its history, architecture and applications followed by capabilities of CIo T in real world and description of machine learning (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. Explains integration of Machine Learning in Io T for building an efficient decision support system Covers Io T, CIo T, 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, Robotics Includes programming codes in Python/Matlab/R alongwith practical examples, questions and multiple choice questions
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