Handbook of Research on Machine Learning Handbook of Research on Machine Learning

Handbook of Research on Machine Learning

Foundations and Applications

Monika Mangla and Others
    • $82.99
    • $82.99

Publisher Description

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.

GENRE
Computing & Internet
RELEASED
2022
4 August
LANGUAGE
EN
English
LENGTH
564
Pages
PUBLISHER
Apple Academic Press
SELLER
Taylor & Francis Group
SIZE
59.4
MB

More Books Like This

Data Science and Data Analytics Data Science and Data Analytics
2021
Machine Learning, Image Processing, Network Security and Data Sciences Machine Learning, Image Processing, Network Security and Data Sciences
2023
Advanced Computational Techniques for Sustainable Computing Advanced Computational Techniques for Sustainable Computing
2022
Intelligent Data Engineering and Automated Learning – IDEAL 2022 Intelligent Data Engineering and Automated Learning – IDEAL 2022
2022
Data Science and Its Applications Data Science and Its Applications
2021
Artificial Intelligence and Technologies Artificial Intelligence and Technologies
2021

More Books by Monika Mangla, Subhash K. Shinde, Vaishali Mehta, Nonita Sharma & Sachi Nandan Mohanty

Challenges and Opportunities for Deep Learning Applications in Industry 4.0 Challenges and Opportunities for Deep Learning Applications in Industry 4.0
2022
Big Data Analytics in Intelligent IoT and Cyber-Physical Systems Big Data Analytics in Intelligent IoT and Cyber-Physical Systems
2023
Cyber-Physical Systems Cyber-Physical Systems
2022
Cyber Security Threats and Challenges Facing Human Life Cyber Security Threats and Challenges Facing Human Life
2022
Real-Life Applications of the Internet of Things Real-Life Applications of the Internet of Things
2022
Emerging Technologies for Healthcare Emerging Technologies for Healthcare
2021