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Machine Learning and the Internet of Things in Education

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Cover of 'Machine Learning and the Internet of Things in Education'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Machine Learning and IoT
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    Chapter 2 Deep Convolutional Network for Food Image Identification
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    Chapter 3 Face Mask Recognition System-Based Convolutional Neural Network
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    Chapter 4 Fuzzy Inference System Based-AI for Diagnosis of Esophageal Cancer
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    Chapter 5 Skin Detection System Based Fuzzy Neural Networks for Skin Identification
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    Chapter 6 Machine Learning Based Cardless ATM Using Voice Recognition Techniques
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    Chapter 7 Automated Classification of Cardiac Arrhythmias
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    Chapter 8 A Fuzzy Logic Implemented Classification Indicator for the Diagnosis of Diabetes Mellitus in TRNC
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    Chapter 9 Implementation and Evaluation of a Mobile Smart School Management System—NEUKinderApp
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    Chapter 10 The Emerging Benefits of Gamification Techniques
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    Chapter 11 A Comprehensive Review of Virtual E-Learning System Challenges
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    Chapter 12 A Semantic Portal to Improve Search on Rivers State’s Independent National Electoral Commission
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    Chapter 13 Implementation of Semantic Web Service and Integration of e-Government Based Linked Data
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    Chapter 14 Application of Zero-Trust Networks in e-Health Internet of Things (IoT) Deployments
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    Chapter 15 IoT Security Based Vulnerability Assessment of E-learning Systems
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    Chapter 16 Blockchain Technology, Artificial Intelligence, and Big Data in Education
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    Chapter 17 Sustainable Education Systems with IOT Paradigms
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    Chapter 18 Post Covid Era-Smart Class Environment
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Title
Machine Learning and the Internet of Things in Education
Published by
Springer Nature Switzerland, November 2023
DOI 10.1007/978-3-031-42924-8
ISBNs
978-3-03-142923-1, 978-3-03-142924-8
Editors

Idoko, John Bush, Abiyev, Rahib

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