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Mastering Transformers

You're reading from  Mastering Transformers

Product type Book
Published in Sep 2021
Publisher Packt
ISBN-13 9781801077651
Pages 374 pages
Edition 1st Edition
Languages
Authors (2):
Savaş Yıldırım Savaş Yıldırım
Profile icon Savaş Yıldırım
Meysam Asgari- Chenaghlu Meysam Asgari- Chenaghlu
Profile icon Meysam Asgari- Chenaghlu
View More author details

Table of Contents (16) Chapters

Preface 1. Section 1: Introduction – Recent Developments in the Field, Installations, and Hello World Applications
2. Chapter 1: From Bag-of-Words to the Transformer 3. Chapter 2: A Hands-On Introduction to the Subject 4. Section 2: Transformer Models – From Autoencoding to Autoregressive Models
5. Chapter 3: Autoencoding Language Models 6. Chapter 4:Autoregressive and Other Language Models 7. Chapter 5: Fine-Tuning Language Models for Text Classification 8. Chapter 6: Fine-Tuning Language Models for Token Classification 9. Chapter 7: Text Representation 10. Section 3: Advanced Topics
11. Chapter 8: Working with Efficient Transformers 12. Chapter 9:Cross-Lingual and Multilingual Language Modeling 13. Chapter 10: Serving Transformer Models 14. Chapter 11: Attention Visualization and Experiment Tracking 15. Other Books You May Enjoy

Who this book is for

This book is for deep learning researchers, hands-on NLP practitioners, and machine learning/NLP educators and students who want to start their journey with the transformer architecture. Beginner-level machine learning knowledge and a good command of Python will help you get the most out of this book.

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