Product details:
| ISBN13: | 9781683926429 |
| ISBN10: | 16839264211 |
| Binding: | Paperback |
| No. of pages: | 158 pages |
| Size: | 229x178 mm |
| Weight: | 444 g |
| Language: | English |
| 284 |
Category:
Data Science for IoT Engineers
A Systems Analytics Approach
Edition number: 1
Publisher: Mercury Learning and Information
Date of Publication: 31 December 2021
Normal price:
Publisher's listprice:
EUR 54.95
EUR 54.95
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Short description:
Designed to introduce the concepts of data science to professionals in engineering, physics, mathematics, and allied fields. This is a workbook with MATLAB code that creates a common framework and points out various interconnections related to industry.
Long description:
No detailed description available for "Data Science for IoT Engineers".
Table 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
