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Savaş Yıldırım - Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques

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Savaş Yıldırım Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques
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Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques: summary, description and annotation

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Take a problem-solving approach to learning all about transformers and get up and running in no time by implementing methodologies that will build the future of NLP

Key Features
  • Explore quick prototyping with up-to-date Python libraries to create effective solutions to industrial problems
  • Solve advanced NLP problems such as named-entity recognition, information extraction, language generation, and conversational AI
  • Monitor your models performance with the help of BertViz, exBERT, and TensorBoard
Book Description

Transformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, youll learn how to build various transformer-based NLP applications using the Python Transformers library.

The book gives you an introduction to Transformers by showing you how to write your first hello-world program. Youll then learn how a tokenizer works and how to train your own tokenizer. As you advance, youll explore the architecture of autoencoding models, such as BERT, and autoregressive models, such as GPT. Youll see how to train and fine-tune models for a variety of natural language understanding (NLU) and natural language generation (NLG) problems, including text classification, token classification, and text representation. This book also helps you to learn efficient models for challenging problems, such as long-context NLP tasks with limited computational capacity. Youll also work with multilingual and cross-lingual problems, optimize models by monitoring their performance, and discover how to deconstruct these models for interpretability and explainability. Finally, youll be able to deploy your transformer models in a production environment.

By the end of this NLP book, youll have learned how to use Transformers to solve advanced NLP problems using advanced models.

What you will learn
  • Explore state-of-the-art NLP solutions with the Transformers library
  • Train a language model in any language with any transformer architecture
  • Fine-tune a pre-trained language model to perform several downstream tasks
  • Select the right framework for the training, evaluation, and production of an end-to-end solution
  • Get hands-on experience in using TensorBoard and Weights & Biases
  • Visualize the internal representation of transformer models for interpretability
Who this book is for

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

Table of Contents
  1. From Bag-of-Words to the Transformers
  2. A Hands-On Introduction to the Subject
  3. Autoencoding Language Models
  4. Autoregressive and Other Language Models
  5. Fine-Tuning Language Models for Text Classification
  6. Fine-Tuning Language Models for Token Classification
  7. Text Representation
  8. Working with Efficient Transformers
  9. Cross-Lingual and Multilingual Language Modeling
  10. Serving Transformer Models
  11. Attention Visualization and Experiment Tracking

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Mastering Transformers

Build state-of-the-art models from scratch with advanced natural language processing techniques

Sava Yldrm

Meysam Asgari-Chenaghlu

BIRMINGHAMMUMBAI Mastering Transformers Copyright 2021 Packt Publishing - photo 2

BIRMINGHAMMUMBAI

Mastering Transformers

Copyright 2021 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

Publishing Product Manager: Aditi Gour

Senior Editor: David Sugarman

Content Development Editor: Nathanya Dias

Technical Editor: Arjun Varma

Copy Editor: Safis Editing

Project Coordinator: Aparna Ravikumar Nair

Proofreader: Safis Editing

Indexer: Tejal Daruwale Soni

Production Designer: Alishon Mendonca

First published: September 2021

Production reference: 1290721

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham

B3 2PB, UK.

ISBN 978-1-80107-765-1

www.packt.com

Contributors
About the authors

Sava Yldrmgraduated from the Istanbul Technical University Department of Computer Engineering and holds a Ph.D. degree in Natural Language Processing( NLP). Currently, he is an associate professor at the Istanbul Bilgi University, Turkey, and is a visiting researcher at the Ryerson University, Canada. He is a proactive lecturer and researcher with more than 20 years of experience teaching courses on machine learning, deep learning, and NLP. He has significantly contributed to the Turkish NLP community by developing a lot of open source software and resources. He also provides comprehensive consultancy to AI companies on their R&D projects. In his spare time, he writes and directs short films, and enjoys practicing yoga.

First of all, I would like to thank my dear partner, Aylin Oktay, for her continuous support, patience, and encouragement throughout the long process of writing this book. I would also like to thank my colleagues at the Istanbul Bilgi University, Department of Computer Engineering, for their support.

Meysam Asgari-Chenaghluis an AI manager at Carbon Consulting and is also a Ph.D. candidate at the University of Tabriz. He has been a consultant for Turkey's leading telecommunication and banking companies. He has also worked on various projects, including natural language understanding and semantic search.

First and foremost, I would like to thank my loving and patient wife, Narjes Nikzad-Khasmakhi, for her support and understanding. I would also like to thank my father for his support; may his soul rest in peace.

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