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007			cr |||||||||||
008			200829s2021 flu ob 001 0 eng
010			_a 2020038958
020			_a9781000337860 _q(epub)
020			_a9781003139041 _q(ebook)
020			_z9780367687823 _q(hardback)
020			_z9780367686314 _q(paperback)
040			_aDLC _beng _cDLC _erda _dDLC
042			_apcc
050	0	0	_aTK5105.8857
082	0	0	_a004.67 PER _223
092			_20
100	1		_aPerros, Harry G., _eauthor.
245	1	3	_aAn introduction to IoT analytics / _cHarry G. Perros.
250			_aFirst edition.
264		1	_aBoca Raton : _bCRC Press, _c2021.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490			_3Data Science Series
504			_aIncludes bibliographical references and index.
505	0		_aReview of probability theory -- Simulation techniques -- Hypothesis testing -- Multivariable linear regression -- Time series forecasting -- Dimensionality reduction -- Clustering techniques -- Classification techniques -- Artificial neural networks -- Support vector machines -- Hidden Markov models.
520			_a"An Introduction to IoT Analytics covers techniques that can be used to analyze data from IoT sensors and also addresses questions regarding the performance of an IoT system. It strikes a balance between practice and theory so that one can learn how to apply these tools in practice with a good understanding of their inner workings. It is an introductory book for readers that have no familiarity with these techniques. The techniques presented in the book come from the areas of Machine Learning, Statistics, and Operations Research. Machine Learning techniques are described that can be used to analyze IoT data generated from sensors for clustering, classification, and regression. The statistical techniques described can be used to carry out regression and forecasting of IoT sensor data, and dimensionality reduction of data sets. Operations Research is concerned with the performance of an IoT system by constructing a model of a system under study, and then carry out what-if analysis. The book also describes simulation techniques. Key features: IoT analytics is not just Machine Learning but it also involves other tools, such as, forecasting and simulation techniques. Many diagrams and examples are given throughout the book to better explain the material presented. At the end of each chapter, there is a project designed to help the reader to better understand the techniques described in the chapter. The material is this book has been class tested over several semesters"-- _cProvided by publisher.
588			_aDescription based on print version record and CIP data provided by publisher.
650		0	_aInternet of things.
650		0	_aSystem analysis.
650		0	_aSystem analysis _xStatistical methods.
650		0	_aOperations research.
776	0	8	_iPrint version: _aPerros, Harry G.. _tAn introduction to IoT analytics _bFirst edition. _dBoca Raton : CRC Press, 2021. _z9780367687823 _w(DLC) 2020038957
843			_aPhotocopy
887			_2CamTech Library
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _n0
999			_c512 _d512