From curve fitting to machine learning [electronic resource] : an illustrative guide to scientific data analysis and computational intelligence / Achim Zielesny.
2016
Q180.55.S7
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Citation
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Unlimited
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Can lend chapters, not whole ebooks
Details
Title
From curve fitting to machine learning [electronic resource] : an illustrative guide to scientific data analysis and computational intelligence / Achim Zielesny.
Author
Edition
Second edition.
ISBN
9783319325453 (electronic book)
3319325450 (electronic book)
9783319325446 print
3319325450 (electronic book)
9783319325446 print
Published
Switzerland : Springer, 2016.
Language
English
Description
1 online resource (xv, 498 pages) : illustrations.
Item Number
10.1007/978-3-319-32545-3 doi
Call Number
Q180.55.S7
Dewey Decimal Classification
507.2/7
Summary
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).
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 19, 2016).
Series
Intelligent systems reference library ; v. 109.
Available in Other Form
Print version: 9783319325446
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Record Appears in
Table of Contents
Introduction
Curve Fitting
Clustering
Machine Learning
Discussion
CIP -Computational Intelligence Packages.
Curve Fitting
Clustering
Machine Learning
Discussion
CIP -Computational Intelligence Packages.