From Curve Fitting to Machine Learning (Record no. 79316)

000 -LEADER
fixed length control field 04366nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-3-319-32545-3
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220801221124.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160413s2016 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319325453
-- 978-3-319-32545-3
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Zielesny, Achim.
245 10 - TITLE STATEMENT
Title From Curve Fitting to Machine Learning
Sub Title An Illustrative Guide to Scientific Data Analysis and Computational Intelligence /
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2016.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XV, 498 p. 343 illus., 200 illus. in color.
490 1# - SERIES STATEMENT
Series statement Intelligent Systems Reference Library,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Curve Fitting -- Clustering -- Machine Learning -- Discussion -- CIP -Computational Intelligence Packages.
520 ## - SUMMARY, ETC.
Summary, etc 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).
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-319-32545-3
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2016.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering mathematics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering—Data processing.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Quantitative research.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical optimization.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical and Computational Engineering Applications.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Analysis and Big Data.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Optimization.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1868-4408 ;
912 ## -
-- ZDB-2-ENG
912 ## -
-- ZDB-2-SXE

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