가야대학교 분성도서관
주메뉴
자료검색
- Home
- 상세정보
상세정보
부가기능
Transformers for machine learning : a deep dive /
상세 프로파일
| 자료유형 | E-Book |
|---|---|
| 개인저자 | Kamath, Uday, author. Graham, Kenneth L., author. Emara, Wael, author. |
| 서명/저자사항 | Transformers for machine learning :a deep dive /Uday Kamath, Kenneth L. Graham, Wael Emara. |
| 판사항 | First edition. |
| 발행사항 | Boca Raton : CRC Press, Taylor & Francis Group, 2022. |
| 형태사항 | 1 online resource (xxv, 257 pages) : illustrations. |
| 총서사항 | Chapman & Hall/CRC machine learning & pattern recognition |
| 소장본 주기 | OCLC control number change |
| ISBN | 9781003170082 1003170080 9781000587074 100058707X 9781000587098 1000587096 |
| 기타표준부호 | 10.1201/9781003170082doi |
| 서지주기 | Includes bibliographical references and index. |
| 내용주기 | List of Figures -- List of Tables -- Author Bios -- Foreword -- Preface -- Contributors -- Chapter 1 Deep Learning and Transformers: An Introduction -- Chapter 2 Transformers: Basics and Introduction -- Chapter 3 Bidirectional Encoder Representations from Transformers (BERT) -- Chapter 4 Multilingual Transformer Architectures -- Chapter 5 Transformer Modifications -- Chapter 6 Specific Transformers -- Chapter 7 Techniques for Transformers -- Bibliography -- Alphabetical Index |
| 요약 | 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. |
| 일반주제명 | Neural networks (Computer science) Computational intelligence. Machine learning. Neural Networks, Computer Re?seaux neuronaux (Informatique) Intelligence informatique. Apprentissage automatique. COMPUTERS -- Neural Networks. COMPUTERS -- Natural Language Processing. COMPUTERS -- Computer Vision & Pattern Recognition. Computational intelligence. Machine learning. Neural networks (Computer science) |
| 언어 | 영어 |
| 기타형태 저록 | Print version :9780367771652 |
| 대출바로가기 | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3259078 |
소장정보
- 소장정보
인쇄
| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00029218 | 006.3/2 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
|
카피라이터
