Data Science for IoT Engineers - A Systems Analytics Approach

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List of contents

Part One
1: Machine Learning from Multiple Perspectives
2: Introduction to Machine Learning
3: Systems Theory, Linear Algebra, and Analytics Basics
4: Modern Machine Learning
Part Two: Systems Analytics
5: Systems Theory Foundations of Machine Learning
6: State Space Model and Bayes Filter
7: The Kalman Filter for Adaptive Machine Learning
8: The Need for Dynamical Machine Learning
9: Digital Twins
Epilogue: A New Random Field Theory
Index

About the author

P. G. Madhavan, Ph.D., has an extensive background in the Internet of Things (IoT), machine learning, digital twins, and wireless technologies in roles such as Chief IoT Officer and IoT Product Manager at large corporations (including Rockwell Automation, GE Aviation, and NEC).

Product details

• Authors: P. G. Madhavan
• Publisher: De Gruyter
• Languages: English
• Product format: Paperback / Softback
• Released: 31.12.2021
• EAN: 9781683926429
• ISBN: 978-1-68392-642-9
• No. of pages: 158
• Dimensions: 178 mm x 9 mm x 229 mm
• Weight: 300 g
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > Programming languages