Machine Learning and the Internet of Things in Education: Models and Applications: 1115 2023rd Edition

Machine Learning and the Internet of Things in Education: Models and Applications: 1115 2023rd Edition book cover

Machine Learning and the Internet of Things in Education: Models and Applications: 1115 2023rd Edition

Author(s): John Bush Idoko (Editor), Rahib Abiyev

  • Publisher: Springer
  • Publication Date: 3 Oct. 2024
  • Edition: 2023rd
  • Language: English
  • Print length: 289 pages
  • ISBN-10: 3031429265
  • ISBN-13: 9783031429262

Book Description

This book is designed to provide rich research hub for researchers, teachers, and students to ease research hassle/challenges. The book is rich and comprehensive enough to provide answers to frequently asked research questions because the content of the book touches several disciplines cutting across computing, engineering, medicine, education, and sciences in general. The rich multidisciplinary contents of the book promise to leave all users satisfied. The valuable features in the book include but not limited to: demonstration of mathematical expressions for implementation of machine learning models, integration of learning techniques, and projection of future AI and IoT technologies. These technologies will enable systems to be simulative, predictive, and self-operating smart systems. The primary audience of the book include but not limited to researchers, teachers, and postgraduate and undergraduate students in computing, engineering, medicine, education, and science fields.

Editorial Reviews

From the Back Cover

This book is designed to provide rich research hub for researchers, teachers, and students to ease research hassle/challenges. The book is rich and comprehensive enough to provide answers to frequently asked research questions because the content of the book touches several disciplines cutting across computing, engineering, medicine, education, and sciences in general. The rich multidisciplinary contents of the book promise to leave all users satisfied. The valuable features in the book include but not limited to: demonstration of mathematical expressions for implementation of machine learning models, integration of learning techniques, and projection of future AI and IoT technologies. These technologies will enable systems to be simulative, predictive, and self-operating smart systems. The primary audience of the book include but not limited to researchers, teachers, and postgraduate and undergraduate students in computing, engineering, medicine, education, and science fields.

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