MARC details
| 000 -LEADER |
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| fixed length control field |
01978nam a22003137a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250225113805.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250224b |||||||| |||| 00| 0 hin d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783031296413 |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
NISER LIBRARY |
| Language of cataloging |
eng |
| Transcribing agency |
NISER LIBRARY |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
004.032.26 |
| Item number |
AGG-N |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Aggarwal, Charu C. |
| 245 ## - TITLE STATEMENT |
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| Title |
Neural networks and deep learning : |
| Remainder of title |
a textbook |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd edition |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc. |
Cham : |
| Name of publisher, distributor, etc. |
Springer, |
| Date of publication, distribution, etc. |
2023. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxiv, 529 pages. : |
| Other physical details |
illustrations (128 b/w illustrations, 22 illustrations in colour) |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references and index |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Deep learning methods for various data domains, such as text, images, and graphs are presented in detail. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Neural networks (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Deep learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Artificial intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Pre-trained language models |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Reinforcement learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Recurrent neural networks |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Table of content |
| Uniform Resource Identifier |
<a href="https://link.springer.com/content/pdf/bfm:978-3-031-29642-0/1">https://link.springer.com/content/pdf/bfm:978-3-031-29642-0/1</a> |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Reviews |
| Uniform Resource Identifier |
<a href="https://www.goodreads.com/book/show/143376276-neural-networks-and-deep-learning?ref=nav_sb_ss_1_13#CommunityReviews">https://www.goodreads.com/book/show/143376276-neural-networks-and-deep-learning?ref=nav_sb_ss_1_13#CommunityReviews</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Universal Decimal Classification |
| Koha item type |
Book |
