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An Introduction to IoT Analytics (Paperback)
Loot Price: R1,571
Discovery Miles 15 710
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An Introduction to IoT Analytics (Paperback)
Series: Chapman & Hall/CRC Data Science Series
Expected to ship within 10 - 15 working days
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This book covers techniques that can be used to analyze data from
IoT sensors and addresses questions regarding the performance of an
IoT system. It strikes a balance between practice and theory so one
can learn how to apply these tools in practice with a good
understanding of their inner workings. This is an introductory book
for readers who have no familiarity with these techniques. The
techniques presented in An Introduction to IoT Analytics 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 the system under study and then
carrying out a what-if analysis. The book also describes simulation
techniques. Key Features IoT analytics is not just machine learning
but also involves other tools, such as forecasting and simulation
techniques. Many diagrams and examples are given throughout the
book to fully explain the material presented. Each chapter
concludes with a project designed to help readers better understand
the techniques described. The material in this book has been class
tested over several semesters. Practice exercises are included with
solutions provided online at www.routledge.com/9780367686314 Harry
G. Perros is a Professor of Computer Science at North Carolina
State University, an Alumni Distinguished Graduate Professor, and
an IEEE Fellow. He has published extensively in the area of
performance modeling of computer and communication systems.
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