Machine Learning in Cognitive IoT
This book covers the different technologies of the 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 the real world and a 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.
- Helps analysts and developers work efficiently with emerging technologies such as data analytics, data processing, Big Data, Robotics.
- Includes programming codes in Python/Matlab/R along with practical examples, questions, and multiple-choice questions.
This book covers the different technologies of the 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 the real world and a 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.
- Helps analysts and developers work efficiently with emerging technologies such as data analytics, data processing, Big Data, Robotics.
- Includes programming codes in Python/Matlab/R along with practical examples, questions, and multiple-choice questions.
Original: $118.17
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$41.36Description
This book covers the different technologies of the 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 the real world and a 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.
- Helps analysts and developers work efficiently with emerging technologies such as data analytics, data processing, Big Data, Robotics.
- Includes programming codes in Python/Matlab/R along with practical examples, questions, and multiple-choice questions.
