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Machine learning with R

Ghatak, Abhijit.

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Machine learning with R

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning with R/ by Abhijit Ghatak.
Author:	Ghatak, Abhijit.
Published:	Singapore :Springer Singapore : : 2017.,
Description:	xix, 210 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-6808-9
ISBN:	9789811068089

Machine learning with R
Ghatak, Abhijit.

Machine learning with R[electronic resource] /by Abhijit Ghatak. - Singapore :Springer Singapore :2017. - xix, 210 p. :ill., digital ;24 cm.

This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it's applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning. In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications. In the process, it touches upon the specifics of each algorithm and the science behind its formulation. The book includes a wealth of worked-out examples along with R codes. It explains the code for each algorithm, and readers can modify the code to suit their own needs. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis. Further, it will be particularly useful and informative for anyone who has struggled to relate the concepts of mathematics and statistics to machine learning.

ISBN: 9789811068089

Standard No.: 10.1007/978-981-10-6808-9doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning with R
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100 1 $a Ghatak, Abhijit. $3 3269811
245 1 0 $a Machine learning with R $h [electronic resource] / $c by Abhijit Ghatak.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2017.
300 $a xix, 210 p. : $b ill., digital ; $c 24 cm.
520 $a This book helps readers understand the mathematics of machine learning, and apply them in different situations. It is divided into two basic parts, the first of which introduces readers to the theory of linear algebra, probability, and data distributions and it's applications to machine learning. It also includes a detailed introduction to the concepts and constraints of machine learning and what is involved in designing a learning algorithm. This part helps readers understand the mathematical and statistical aspects of machine learning. In turn, the second part discusses the algorithms used in supervised and unsupervised learning. It works out each learning algorithm mathematically and encodes it in R to produce customized learning applications. In the process, it touches upon the specifics of each algorithm and the science behind its formulation. The book includes a wealth of worked-out examples along with R codes. It explains the code for each algorithm, and readers can modify the code to suit their own needs. The book will be of interest to all researchers who intend to use R for machine learning, and those who are interested in the practical aspects of implementing learning algorithms for data analysis. Further, it will be particularly useful and informative for anyone who has struggled to relate the concepts of mathematics and statistics to machine learning.
650 0 $a Machine learning. $3 533906
650 0 $a R (Computer program language) $3 784593
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Programming Techniques. $3 892496
650 2 4 $a Programming Languages, Compilers, Interpreters. $3 891123
650 2 4 $a Database Management. $3 891010
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-6808-9
950 $a Computer Science (Springer-11645)