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Intelligent techniques for data science

Akerkar, Rajendra.

Intelligent techniques for data science

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent techniques for data scienceby Rajendra Akerkar, Priti Srinivas Sajja.
Author:	Akerkar, Rajendra.
other author:	Sajja, Priti Srinivas.
Published:	Cham :Springer International Publishing :2016.
Description:	xvi, 272 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Quantitative research.
Online resource:	http://dx.doi.org/10.1007/978-3-319-29206-9
ISBN:	9783319292069$q(electronic bk.)

Intelligent techniques for data science
Akerkar, Rajendra.

Intelligent techniques for data science[electronic resource] /by Rajendra Akerkar, Priti Srinivas Sajja. - Cham :Springer International Publishing :2016. - xvi, 272 p. :ill. (some col.), digital ;24 cm.

Preface -- Introduction -- Data Analytics -- Basic Learning Algorithms -- Fuzzy Logic -- Artificial Neural Networks -- Genetic Algorithms and Evolutionary Computing -- Other Metaheuristics and Classification Approaches -- Analytics and Big Data -- Data Analytics Using R -- Appendix I: Tools for Data Science -- Appendix II: Tools for Computational Intelligence.

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions. The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

ISBN: 9783319292069$q(electronic bk.)

Standard No.: 10.1007/978-3-319-29206-9doiSubjects--Topical Terms:

367894
Quantitative research.

LC Class. No.: Q180.55.Q36

Dewey Class. No.: 001.42

Intelligent techniques for data science
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505 0 $a Preface -- Introduction -- Data Analytics -- Basic Learning Algorithms -- Fuzzy Logic -- Artificial Neural Networks -- Genetic Algorithms and Evolutionary Computing -- Other Metaheuristics and Classification Approaches -- Analytics and Big Data -- Data Analytics Using R -- Appendix I: Tools for Data Science -- Appendix II: Tools for Computational Intelligence.
520 $a This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions. The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.
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