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003			Ost
005			20250319071053.0
008			220224s2023 flua bf 001 0 eng
010			_a 2022000102
020			_a9781774638682 _q(hardcover)
020			_a9781774638699 _q(paperback)
020			_z9781003277330 _q(ebook)
040			_aBSULIB _beng _erda _cBSU _dBSU
042			_apcc
050	0	0	_aQ325.5 _b.H3623 2023
082	0	0	_a226.3 _223 _bBEA
245	0	0	_aHandbook of research on machine learning : _bfoundations and applications / _cedited by Monika Mangla, PhD, Subhash K. Shinde, PhD, Vaishali Mehta, PhD, Nonita Sharma, PhD, Sachi Nandan Mohanty, PhD.
250			_aFirst edition.
260			_aUSA _bBaker Academic _cc2011
300			_axxx, 564 pages : _billustrations (some color) ; _c24 cm
504			_aIncludes bibliographical references and index.
520			_a"With over 250 figures, tables, and charts, this volume takes the reader on a technological voyage of machine learning (ML) 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 first section the Handbook of Research on Machine Learning: Foundations and Applications provides an overview of the ethics, security and privacy issues, future directions, and challenges in machine learning. The section also presents a systematic review of deep learning techniques and provides an understanding of building generative adversarial networks. The second section of the volume focuses on the applications of machine learning in healthcare, emphasizing its current status, analytics, and future prospects. Chapters explore predictive data analytics for health issues, the detection of infectious diseases in human bodies, time series forecasting techniques for infectious disease prediction, as well as a review of medical analytics using social media. Section 3 adds a macro dimension to the book 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. The plethora of topics covered in the Handbook of Research on Machine Learning: Foundations and Applications will give readers a thorough look into the vast applications of machine learning. It will familiarize researchers and scientists as well as faculty and students with the latest trends in machine learning starting from rudiments and then delving into its applications in healthcare and other industries"--
650		0	_aMachine learning. _925097
700	1		_aMangla, Monika, _eeditor. _925098
776	0	8	_iOnline version: _tHandbook of research on machine learning _bFirst edition _dPalm Bay, FL, USA : Apple Academic Press, 2022 _z9781003277330 _w(DLC) 2022000103
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
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