Transformers for machine learning : (Record no. 141323)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02249nam a22002657a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260707171344.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 260707s2022 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780367767341 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | PK-LaUMT |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.32 |
| 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 | Uday Kamath, Kenneth L. Graham and Wael Emara |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc | Boca Raton : |
| Name of publisher, distributor, etc | CRC Press, |
| Date of publication, distribution, etc | 2022 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxv, 257 p. |
| 490 ## - SERIES STATEMENT | |
| Series statement | Chapman & Hall/CRC machine learning & pattern recognition series |
| 500 ## - GENERAL NOTE | |
| General note | Includes bibliographical references and index. |
| 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. Key Features: A comprehensive reference book for detailed explanations for every algorithm and techniques related to the transformers. 60+ transformer architectures covered in a comprehensive manner. A book for understanding how to apply the transformer techniques in speech, text, time series, and computer vision. Practical tips and tricks for each architecture and how to use it in the real world. Hands-on case studies and code snippets for theory and practical real-world analysis using the tools and libraries, all ready to run in Google Colab. 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 |
| 546 ## - LANGUAGE NOTE | |
| Language note | Eng |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Neural networks (Computer science) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational intelligence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine Learning |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Graham, Kenneth L. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Emara, Wael |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Home library | Current library | Date acquired | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|
| UMT Main Campus | UMT Main Campus | 2026-07-07 | 006.32 KAM-T | 153252 | 2026-07-07 | 2026-07-07 | Books |