Transformers for machine learning a deep dive / Uday Kamath, Kenneth Graham, Wael Emara.
| Author/creator | Kamath, Uday |
| Format | Electronic |
| Edition | First edition. |
| Publication Info | Boca Raton : CRC Press, 2022. |
| Description | pages cm |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Supplemental Content | Full text available from Taylor & Francis eBooks |
| Subjects |
| Abstract | "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"-- Provided by publisher. |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2021059529 |
| ISBN | 9780367771652 (hardback) |
| ISBN | 9780367767341 (paperback) |
| ISBN | (ebook) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |