From Curve Fitting to Machine Learning

An Illustrative Guide to Scientific Data Analysis and Computational Intelligence

  • Achim Zielesny

Part of the Intelligent Systems Reference Library book series (ISRL, volume 109)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Achim Zielesny
    Pages 1-59
  3. Achim Zielesny
    Pages 61-155
  4. Achim Zielesny
    Pages 157-228
  5. Achim Zielesny
    Pages 229-406
  6. Achim Zielesny
    Pages 407-435
  7. Back Matter
    Pages 437-498

About this book


This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics.
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).


Computational Intelligence Machine Learning Data Analysis Mathematical Optimization Evolutionary Algorithms

Authors and affiliations

  • Achim Zielesny
    • 1
  1. 1.Ins. für biologische & chemische Info.Westfälische HochschuleRecklinghausenGermany

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-32544-6
  • Online ISBN 978-3-319-32545-3
  • Series Print ISSN 1868-4394
  • Series Online ISSN 1868-4408
  • Buy this book on publisher's site
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