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| 001 | 21730789 | ||
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| 008 | 200829s2021 flua b 001 0 eng | ||
| 010 | _a 2020038957 | ||
| 020 |
_a9780367687823 _q(hardback) |
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| 020 |
_a9780367686314 _q(paperback) |
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| 020 |
_z9781003139041 _q(ebook) |
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| 035 | _a21730789 | ||
| 040 |
_aLBSOR/DLC _beng _cDLC _erda _dDLC |
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| 042 | _apcc | ||
| 050 | 0 | 0 |
_aTK5105.8857 _b.P47 2021 |
| 082 | 0 | 0 |
_a004.678 P.H.A 2021 _223 |
| 100 | 1 |
_aPerros, Harry G., _eauthor. |
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| 245 | 1 | 3 |
_aAn introduction to IoT analytics / _cHarry G. Perros. |
| 250 | _aFirst edition. | ||
| 264 | 1 |
_aBoca Raton : _bCRC Press, Taylor & Francis Group, _c2021. |
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| 300 |
_axvii, 354 pages : _bcolor illusstrations ; _c26 cm |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_aunmediated _bn _2rdamedia |
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| 338 |
_avolume _bnc _2rdacarrier |
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| 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. |
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| 650 | 0 | _aInternet of things. | |
| 650 | 0 | _aSystem analysis. | |
| 650 | 0 |
_aSystem analysis _xStatistical methods. |
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| 650 | 0 | _aOperations research. | |
| 776 | 0 | 8 |
_iOnline version: _aPerros, Harry G. _tIntroduction to IoT analytics. _bFirst edition _dBoca Raton : CRC Press, 2021 _z9781003139041 _w(DLC) 2020038958 |
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2ddc _cBK _n0 |
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| 999 |
_c161 _d161 |
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