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Handbook of Research on Machine Learning: Foundations and Applications

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This volume takes the reader on a technological voyage of machine learning advancements, highlighting the systematic changes in algorithms, challenges, and constraints. The technological advancements in the ML arena have transformed and revolutionized several fields, including transportation, agriculture, finance, weather monitoring, and others. This book brings together researchers, authors, industrialists, and academicians to cover a vast selection of topics in ML, starting with the rudiments of machine learning approaches and going on to specific applications in healthcare and industrial automation.

The book begins with an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning as well as a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. Chapters explore predictive data analytics for health issues. The book also adds a macro dimension by highlighting the industrial applications of machine learning, such as in the steel industry, for urban information retrieval, in garbage detection, in measuring air pollution, for stock market predictions, for underwater fish detection, as a fake news predictor, and more.

Author(s): Monika Mangla, Subhash K. Shinde, Vaishali Mehta, Nonita Sharma, Sachi Nandan Mohanty
Publisher: CRC Press/Apple Academic Press
Year: 2022

Language: English
Pages: 564
City: Palm Bay

Cover Page
Half Title Page
Title Page
Copyright Page
About the Editors
Table of Contents
Contributors
Abbreviations
Acknowledgments
Preface
Part I: Rudiments of Machine Learning Approaches
1 Ethics in AI in Machine Learning
2 Advances in Artificial Intelligence Models for Providing Security and Privacy Using Machine Learning Technique
3 A Systematic Review of Deep Learning Techniques for Semantic Image Segmentation: Methods, Future Directions, and Challenges
4 Covariate Shift in Machine Learning
5 Understanding and Building Generative Adversarial Networks
Part II: Application of Machine Learning in Healthcare
6 Machine Learning in Healthcare: Applications, Current Status, and Future Prospects
7 Employing Machine Learning for Predictive Data Analytics in Healthcare
8 Prediction of Heart Disease Using Machine Learning
9 Detection of Infectious Diseases in Human Bodies by Using Machine Learning Algorithms
10 Medical Review Analytics Using Social Media
11 Time Series Forecasting Techniques for Infectious Disease Prediction
Part III: Towards Industrial Automation Through Machine Learning
12 Machine Learning in the Steel Industry
13 Experiments Synergizing Machine Learning Approaches with Geospatial Big Data for Improved Urban Information Retrieval
14 Garbage Detection Using SURF Algorithm Based on Merchandise Marker
15 Evolution of Long Short-Term Memory (LSTM) in Air Pollution Forecasting
16 Application of Machine Learning in Stock Market Prediction
17 Deep Learning Model for Stochastic Analysis and Time-Series Forecasting of Indian Stock Market
18 Enhanced Fish Detection in Underwater Video Using Wavelet-Based Color Correction and Machine Learning
19 Fake News Predictor Model-Based on Machine Learning and Natural Language Processing
20 Machine Learning on Simulation Tools for Underwater Sensor Network
21 Prediction and Analysis of Heritage Monuments Images Using Machine Learning Techniques
Index