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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
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)