This book 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.
This book 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.
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 modelling of computer and communication systems, and in his free time he likes to go sailing and play the bouzouki.
Inhaltsangabe
1. Introduction 2. Review of Probability Theory 3. Simulation Techniques 4. Hypothesis Testing 5. Multivariable Linear Regression 6. Time Series Forecasting 7. Dimensionality Reduction 8. Clustering Techniques 9. Classification Techniques 10. Artificial Neural Networks 11. Support Vector Machines 12. Hidden Markov Models