Mathematics and R programming for machine learning : (Record no. 18817)

MARC details
000 -LEADER
fixed length control field 04464cam a22006011i 4500
001 - CONTROL NUMBER
control field 9781003051220
003 - CONTROL NUMBER IDENTIFIER
control field FlBoTFG
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220724194543.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200818t20202021flua ob 000 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency OCoLC-P
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency OCoLC-P
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000196993
Qualifying information (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000196992
Qualifying information (ePub ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000196979
Qualifying information (PDF ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000196976
Qualifying information (PDF ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781000196986
Qualifying information (Mobipocket ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1000196984
Qualifying information (Mobipocket ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781003051220
Qualifying information (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 1003051227
Qualifying information (ebook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367561949 (hbk.)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Canceled/invalid ISBN 9780367507855 (pbk.)
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1201/9781003051220
Source of number or code doi
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)1198598560
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC-P)1198598560
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .C53 2020eb
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 051300
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 051210
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UY
Source bicssc
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Claster, William B.,
Relator term author.
245 10 - TITLE STATEMENT
Title Mathematics and R programming for machine learning :
Remainder of title from the ground up /
Statement of responsibility, etc. William B. Claster.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Boca Raton, FL :
Name of producer, publisher, distributor, manufacturer CRC Press,
Date of production, publication, distribution, manufacture, or copyright notice 2020.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2021
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource :
Other physical details illustrations (black and white)
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
336 ## - CONTENT TYPE
Content type term still image
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Source rdacarrier
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note <P>Chapter 1. Functions Tutorial. Chapter 2. Logic and R. Chapter 3. Sets with R: Building the Tools. Chapter 4. Probability. Chapter 5. Naïve Rule. Chapter 6. Complete Bayes. Chapter 7. Naïve Bayes Classifier. Chapter 8. Stored Model for Naive Bayes Classifier. Chapter 9. Review of Mathematics for Neural Networks. Chapter 10. Calculus. Chapter 11. Neural Networks -- Feed Forward Process and Back Propagation Process. Chapter 12. Programming a Neural Network using OOP in R. Chapter 13. Adding in a Bias Term. Chapter 14. Modular Version of Neural Networks for Deep Learning. Chapter 15. Deep Learning with Convolutional Neural Networks. Chapter 16. R Packages for Neural Networks, Deep Learning, and Naïve Bayes.</P>
520 ## - SUMMARY, ETC.
Summary, etc. Based on the author's experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning with R: From the Ground Up reveals how machine learning algorithms do their magic and explains how these algorithms can be implemented in code. It is designed to provide readers with an understanding of the reasoning behind machine learning algorithms as well as how to program them. Written for novice programmers, the book progresses step-by-step, providing the coding skills needed to implement machine learning algorithms in R. The book begins with simple implementations and fundamental concepts of logic, sets, and probability before moving to the coverage of powerful deep learning algorithms. The first eight chapters deal with probability-based machine learning algorithms, and the last eight chapters deal with machine learning based on artificial neural networks. The first half of the book does not require mathematical sophistication, although familiarity with probability and statistics would be helpful. The second half assumes the reader is familiar with at least one semester of calculus. The text guides novice R programmers through algorithms and their application and along the way; the reader gains programming confidence in tackling advanced R programming challenges. Highlights of the book include: More than 400 exercises A strong emphasis on improving programming skills and guiding beginners to the implementation of full-fledged algorithms Coverage of fundamental computer and mathematical concepts including logic, sets, and probability In-depth explanations of machine learning algorithms
588 ## - SOURCE OF DESCRIPTION NOTE
Source of description note OCLC-licensed vendor bibliographic record.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element R (Computer program language)
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Programming (Mathematics)
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTERS / Artificial Intelligence
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTERS / Programming / Algorithms
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTERS / Programming / Object Oriented
Source of heading or term bisacsh
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Read Online
Uniform Resource Identifier <a href="https://www.taylorfrancis.com/books/9781003051220">https://www.taylorfrancis.com/books/9781003051220</a>
856 42 - ELECTRONIC LOCATION AND ACCESS
Materials specified OCLC metadata license agreement
Uniform Resource Identifier <a href="http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf">http://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type eBook

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