ABSTRACT

This book covers the different technologies of Internet, and machine learning capabilities involved in Cognitive Internet of Things (CIoT). 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 IoT basics, its history, architecture and applications followed by capabilities of CIoT 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 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, Robotics
  • Includes programming codes in Python/Matlab/R alongwith practical examples, questions and multiple choice questions

chapter 1|26 pages

Internet of Things

chapter 2|19 pages

Cognitive Internet of Things

chapter 3|19 pages

Data Mining in IoT

chapter 4|19 pages

Machine Learning Techniques

chapter 5|35 pages

R Programming

chapter 6|21 pages

Machine Learning Paradigms

chapter 7|16 pages

Different Machine Learning Models

chapter 8|22 pages

Data Processing

chapter 9|44 pages

Feature Engineering and Optimization

chapter 10|18 pages

Evaluation and Validation of Results

chapter 11|6 pages

Solutions

chapter 12|37 pages

Dataset