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Deep learning (Record no. 13717)

000 -LEADER
fixed length control field 01712cam a2200313 i 4500
001 - CONTROL NUMBER
control field 19134018
003 - CONTROL NUMBER IDENTIFIER
control field IIITD
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200103020002.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 160613t20162016maua b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2016022992
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780262035613
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Transcribing agency DLC
Description conventions rda
Modifying agency DLC
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .G66 2016
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
Item number GOO-D
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Goodfellow, Ian
245 10 - TITLE STATEMENT
Title Deep learning
Statement of responsibility, etc Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge, Mass. :
Name of publisher, distributor, etc MIT Press,
Date of publication, distribution, etc ©2016.
300 ## - PHYSICAL DESCRIPTION
Extent xxii, 775 p. :
Other physical details ill. ;
Dimensions 25 cm.
490 0# - SERIES STATEMENT
Series statement Adaptive computation and machine learning
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (pages 711-766) and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Applied math and machine learning basics. Linear algebra -- Probability and information theory -- Numerical computation -- Machine learning basics -- Deep networks: modern practices. Deep feedforward networks -- Regularization for deep learning -- Optimization for training deep models -- Convolutional networks -- Sequence modeling: recurrent and recursive nets -- Practical methodology -- Applications -- Deep learning research. Linear factor models -- Autoencoders -- Representation learning -- Structured probabilistic models for deep learning -- Monte Carlo methods -- Confronting the partition function -- Approximate inference -- Deep generative models.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Bengio, Yoshua
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Courville, Aaron
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c orignew
d 1
e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Books
Koha issues (borrowed), all copies 43
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent Location Current Location Shelving location Date acquired Cost, normal purchase price Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Cost, replacement price Price effective from Koha item type Bill No. Bill Date PO No. PO Date Vendor/Supplier Public note
        Not For Loan Computer Science and Engineering IIITD IIITD Reference 2017-03-16 3733.73 10 2 REF 006.31 GOO-D 007352 2020-01-03 2019-10-24 $80.00 2017-03-16 Books IN13393 2017-03-15 IIITD/LIC/BS/2015/09/44 2017-02-01 Intercontinental Book Agency  
        Not For Loan Computer Science and Engineering IIITD IIITD Staff Office 2017-08-24   14 21 006.31 GOO-D copy13 2020-01-09 2019-12-13   2017-08-24 Reference           Vol.1 (2 volumes set)
        Not For Loan Computer Science and Engineering IIITD IIITD Staff Office 2017-08-24   9 14 006.31 GOO-D copy14 2020-01-02 2020-01-02   2017-08-24 Reference           Vol.2 (2 volumes set)

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