Introduction to Transfer Learning (Record no. 178330)

MARC details
000 -LEADER
fixed length control field 04194nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-981-19-7584-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125455.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 230330s2023 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789811975844
-- 978-981-19-7584-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-981-19-7584-4
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5-.7
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT029000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQM
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Wang, Jindong.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Introduction to Transfer Learning
Medium [electronic resource] :
Remainder of title Algorithms and Practice /
Statement of responsibility, etc by Jindong Wang, Yiqiang Chen.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2023.
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2023.
300 ## - PHYSICAL DESCRIPTION
Extent XXI, 329 p. 1 illus. in color.
Other physical details online resource.
336 ## -
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-- txt
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-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Machine Learning: Foundations, Methodologies, and Applications,
International Standard Serial Number 2730-9916
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Part I. Foundations of Transfer Learning -- Chapter 1. Introduction -- Chapter 2. From Machine Learning to Transfer Learning -- Chapter 3. Overview of Transfer Learning Algorithms -- Chapter 4. Instance Weighting Methods -- Chapter 5. Statistical Feature Transformation Methods -- Chapter 6. Geometrical Feature Transformation Methods -- Chapter 7. Theory, Evaluation, and Model Selection -- Part II. Modern Transfer Leaning -- Chapter 8. Pre-training and Fine-tuning -- Chapter 9. Deep Transfer Learning -- Chapter 10. Adversarial Transfer Learning -- Chapter 11. Generalization in Transfer Learning -- Chapter 12. Safe & Robust Transfer Learning -- Chapter 13. Transfer Learning in Complex Environments -- Chapter 14. Low-resource Learning -- Part III. Applications -- Chapter 15. Transfer Learning for Computer Vision -- Chapter 16. Transfer Learning for Natural language Processing -- Chapter 17. Transfer Learning for Speech Recognition -- Chapter 18. Transfer Learning for Activity Recognition -- Chapter 19. Federated Learning for Personalized Healthcare -- Chapter 20. Concluding Remarks.
520 ## - SUMMARY, ETC.
Summary, etc Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a “student’s” perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural language processing (Computer science).
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory and Algorithms for Application Domains.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Natural Language Processing (NLP).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Chen, Yiqiang.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811975837
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811975851
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811975868
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Machine Learning: Foundations, Methodologies, and Applications,
-- 2730-9916
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-981-19-7584-4">https://doi.org/10.1007/978-981-19-7584-4</a>
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-- ZDB-2-SCS
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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