by Monika Mangla (Editor), Subhash K. Shinde (Editor), Vaishali Mehta (Editor), Nonita Sharma (Editor), Sachi Nandan Mohanty (Editor)
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.
