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Transformers for Natural Language Processing - Second Edition: Build, train, ...

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Book Title
Transformers for Natural Language Processing - Second Edition: Bu
ISBN
9781803247335
Publication Year
2022
Type
Textbook
Format
Trade Paperback
Language
English
Subject Area
Computers, Science
Publication Name
Transformers for Natural Language Processing : Build, Train, and Fine-Tune Deep Neural Network Architectures for NLP with Python, Pytorch, TensorFlow, BERT, and GPT-3
Author
Antonio Gulli, Denis Rothman
Item Length
92.5 in
Publisher
Packt Publishing, The Limited
Item Width
75 in
Subject
General, Desktop Applications / Word Processing
Number of Pages
602 Pages

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Product Information

OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance.Purchase of the print or Kindle book includes a free eBook in PDF format Key Features Improve your productivity with OpenAI's ChatGPT and GPT-4 from prompt engineering to creating and analyzing machine learning models Pretrain a BERT-based model from scratch using Hugging Face Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data Book Description Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs?Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses.You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model.If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides.The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details).You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using DALL-E 2, ChatGPT, and GPT-4.By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective. What you will learn Discover new techniques to investigate complex language problems Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3 Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E Learn the mechanics of advanced prompt engineering for ChatGPT and GPT-4 Who this book is for If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community to help guide you on your transformers journey! ]]>

Product Identifiers

Publisher
Packt Publishing, The Limited
ISBN-10
1803247339
ISBN-13
9781803247335
eBay Product ID (ePID)
19057274844

Product Key Features

Author
Antonio Gulli, Denis Rothman
Publication Name
Transformers for Natural Language Processing : Build, Train, and Fine-Tune Deep Neural Network Architectures for NLP with Python, Pytorch, TensorFlow, BERT, and GPT-3
Format
Trade Paperback
Language
English
Subject
General, Desktop Applications / Word Processing
Publication Year
2022
Type
Textbook
Subject Area
Computers, Science
Number of Pages
602 Pages

Dimensions

Item Length
92.5 in
Item Width
75 in

Additional Product Features

Edition Number
2
Intended Audience
Trade
Lc Classification Number
Q325.73
Dewey Decimal
006.31
Dewey Edition
23

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