The principles of deep learning theory : (Record no. 172601)

MARC details
000 -LEADER
fixed length control field 02374nam a22002777a 4500
003 - CONTROL NUMBER IDENTIFIER
control field IIITD
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240815020005.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240518b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781316519332
040 ## - CATALOGING SOURCE
Original cataloging agency IIITD
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number CB 006.3
Item number ROB-P
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Roberts, Daniel A
245 14 - TITLE STATEMENT
Title The principles of deep learning theory :
Remainder of title an effective theory approach to understanding neural networks
Statement of responsibility, etc by Daniel A. Roberts and Sho Yaida
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New York :
Name of publisher, distributor, etc Cambridge University Press,
Date of publication, distribution, etc ©2022
300 ## - PHYSICAL DESCRIPTION
Extent x, 460 p. :
Other physical details ill ;
Dimensions 26 cm.
500 ## - GENERAL NOTE
General note This book include an index.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 ## - FORMATTED CONTENTS NOTE
Title Pretraining
-- Neural network
-- effective theory of deep linear networks at initialization
-- RG flow of presentations
-- effective theory of the NTK at initialization
-- Kernel learning
-- representation learning
520 ## - SUMMARY, ETC.
Summary, etc "This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics, Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Deep learning (Machine learning)
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element SCIENCE / Physics / Mathematical & Computational
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pretraining
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Yaida, Sho
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Online version:
Main entry heading Roberts, Daniel A.
Title Principles of deep learning theory
Edition 1.
Place, publisher, and date of publication New York : Cambridge University Press, 2022
International Standard Book Number 9781009023405
Record control number (DLC) 2021060636
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
Koha issues (borrowed), all copies 1
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Bill No. Bill Date Cost, normal purchase price PO No. PO Date Total Checkouts Total Renewals Full call number Barcode Date last seen Date checked out Cost, replacement price Price effective from Vendor/Supplier Koha item type Public note
    Dewey Decimal Classification     Computer Science and Engineering IIITD IIITD Reference 18/05/2024 TB439 2024-03-30 4266.15 Email-29-03-2024 2024-03-29 1 1 CB 006.3 ROB-P 012958 13/09/2024 14/08/2024 £ 59.99 18/05/2024 Technical Bureau India Pvt. Ltd. Books DBT Project Grant
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