Deep learning / (Record no. 280956)

000 -LEADER
fixed length control field 04379cam a2200553 i 4500
001 - CONTROL NUMBER
control field ocn955778308
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190517115254.0
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
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 0262035618
029 1# - (OCLC)
OCLC library identifier CHDSB
System control number 006734984
029 1# - (OCLC)
OCLC library identifier CHVBK
System control number 494742062
029 1# - (OCLC)
OCLC library identifier GBVCP
System control number 865398267
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000058466134
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)955778308
Canceled/invalid control number (OCoLC)951226949
-- (OCoLC)964650355
-- (OCoLC)1009034043
040 ## - CATALOGING SOURCE
Original cataloging agency DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
Modifying agency YDXCP
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042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .G66 2016
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Source eflch
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Source ukslc
080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER
Universal Decimal Classification number 004.85
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/1
Edition number 23
084 ## - OTHER CLASSIFICATION NUMBER
Classification number 006.31
Item number GOO
Source of number z
084 ## - OTHER CLASSIFICATION NUMBER
Classification number 006.31
Item number GOO
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Goodfellow, Ian,
Relator term author.
245 10 - TITLE STATEMENT
Title Deep learning /
Statement of responsibility, etc Ian Goodfellow, Yoshua Bengio, and Aaron Courville.
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge, Massachusetts :
Name of publisher, distributor, etc The MIT Press,
Date of publication, distribution, etc [2016]
264 #4 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Date of publication, distribution, etc ©2016
300 ## - PHYSICAL DESCRIPTION
Extent xxii, 775 pages :
Other physical details illustrations (some color) ;
Dimensions 24 cm.
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
490 1# - 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 Introduction -- 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.
520 ## - SUMMARY, ETC.
Summary, etc "Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and video games. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors"--Page 4 of cover.
590 ## - LOCAL NOTE (RLIN)
Local note GRETA POINT: 004.85 GOO
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element MACHINE LEARNING
9 (RLIN) 54225
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element ARTIFICIAL INTELLIGENCE
9 (RLIN) 19624
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS
9 (RLIN) 6828
650 #4 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element INFORMATION TECHNOLOGY
9 (RLIN) 28591
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Bengio, Yoshua,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Courville, Aaron,
Relator term author.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Adaptive computation and machine learning.
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://www.deeplearningbook.org/
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type BOOK
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Permanent Location Current Location Shelving location Date acquired Total Checkouts Total Renewals Full call number Barcode Checked out Date last seen Date checked out Copy number Price effective from Koha item type
          WELLINGTON WELLINGTON BOOKS 2018-09-18 1 3 004.85 GOO B019148 2019-08-23 2018-09-18 2018-09-18 1 2018-09-03 BOOK

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