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.
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