Overview
- Serves as introduction to curve fitting, clustering
- and machine learning along with topics like mathematical optimization or
- evolutionary algorithms
- Outlines all concepts and ideas in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics
- Extended, revised and interactive 2nd edition updated to the use of CIP 2.0 for Mathematica 10
- Includes supplementary material: sn.pub/extras
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 109)
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About this book
The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence.
All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages(CIP), a high-level function library developed with Mathematica's programming language on top of Mathematica's algorithms. CIP is open-source and the detailed code used throughout the book is freely accessible.
The target readerships are students of (computer) science and engineering as well as scientific practitioners in industry and academia who deserve an illustrative introduction. Readers with programming skills may easily port or customize the provided code. "'From curve fitting to machine learning' is ... a useful book. ... It contains the basic formulas of curve fitting and related subjects and throws in, what is missing in so many books, the code to reproduce the results.
All in all this is an interesting and useful book both for novice as well as expert readers. For the novice it is a good introductory book and the expert will appreciate the many examples and working code". Leslie A. Piegl (Review of the first edition, 2012).
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Table of contents (5 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: From Curve Fitting to Machine Learning
Book Subtitle: An Illustrative Guide to Scientific Data Analysis and Computational Intelligence
Authors: Achim Zielesny
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-32545-3
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-32544-6Published: 22 April 2016
Softcover ISBN: 978-3-319-81313-4Published: 22 April 2018
eBook ISBN: 978-3-319-32545-3Published: 13 April 2016
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 2
Number of Pages: XV, 498
Number of Illustrations: 143 b/w illustrations, 200 illustrations in colour
Topics: Artificial Intelligence, Mathematical and Computational Engineering, Data Mining and Knowledge Discovery, Big Data/Analytics, Optimization