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Transformers for Machine Learning: A Deep Dive by Uday Kamath Paperback Book
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- ISBN-13
- 9780367767341
- Book Title
- Transformers for Machine Learning
- ISBN
- 9780367767341
- Publication Year
- 2022
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Mathematics
- Publication Name
- Transformers for Machine Learning
- Publisher
- CRC Press LLC
- Subject
- General
- Number of Pages
- 248 Pages
關於產品
Product Information
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.
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
0367767341
ISBN-13
9780367767341
eBay Product ID (ePID)
4057241096
Product Key Features
Publication Name
Transformers for Machine Learning
Format
Trade Paperback
Language
English
Subject
General
Publication Year
2022
Type
Textbook
Subject Area
Mathematics
Number of Pages
248 Pages
Additional Product Features
LCCN
2021-059529
Lc Classification Number
Qa76.87.K354 2022
Dewey Decimal
006.32
Dewey Edition
23
Illustrated
Yes
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物品所在地：
Calgary, Alberta, 加拿大
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