MARC details
000 -LEADER |
fixed length control field |
02058nam a22002777a 4500 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
IIITD |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240808020004.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
240508b |||||||| |||| 00| 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9780367767341 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
IIITD |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
CB 006.3 |
Item number |
KAM-T |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Kamath, Uday |
245 10 - TITLE STATEMENT |
Title |
Transformers for machine learning : |
Remainder of title |
a deep dive |
Statement of responsibility, etc |
by Uday Kamath, Kenneth L Graham and Wael Emara |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc |
New york : |
Name of publisher, distributor, etc |
Chapman and Hall, |
Date of publication, distribution, etc |
©2022 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xxv, 257 p. : |
Other physical details |
ill. ; |
Dimensions |
23 cm. |
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
Title |
Chapman & Hall/CRC machine learning & pattern recognition |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index. |
505 ## - FORMATTED CONTENTS NOTE |
Title |
Deep Learning and Transformers: An Introduction |
-- |
Transformers: Basics and Introduction |
-- |
Bidirectional Encoder Representations from Transformers (BERT) |
-- |
Multilingual Transformer Architectures |
-- |
Transformer Modifications |
-- |
Pre-trained and Application-Specific Transformers |
-- |
Interpretability and Explainability Techniques for Transformers. |
520 ## - SUMMARY, ETC. |
Summary, etc |
"Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. Transformers for Machine Learning: A Deep Dive is the first comprehensive book on transformers. The theoretical explanations of the state-of-the-art transformer architectures will appeal to postgraduate students and researchers (academic and industry) as it will provide a single entry point with deep discussions of a quickly moving field. The practical hands-on case studies and code will appeal to undergraduate students, practitioners, and professionals as it allows for quick experimentation and lowers the barrier to entry into the field"-- |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Neural networks (Computer science). |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Computational intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning. |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Graham, Kenneth L |
700 ## - ADDED ENTRY--PERSONAL NAME |
Personal name |
Emara, Wael |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Books |
Koha issues (borrowed), all copies |
2 |