Transformers for Natural Language Processing - Second Edition: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4

BLUF: This intermediate-to-advanced text provides a no-holds-barred introduction to transformer architecture and application for NLP (and other) tasks. If you're looking to up your NLP game, this book is for you.PROS:- Helpful background information for computer scientists and data wizards alike- Plenty of graphics and in-depth explanations of the "black boxes" of transformers; especially helpful for the visual learner- Good mix of theory and application with a focus on the latterCONS:- Fairly advanced text; assumes the reader has a certain breadth of subject matter knowledge (definitely not for beginners)

This is a very superficial introduction to the topic. Instead of providing a deep understanding it rather makes prosaic claims of what a revolution transformers are.

the book reads like a compilation of newspaper style articles. there is not much rigour or proper explanation. it seems like a book that is written by copy pasting material from different places without good understanding. full of repetition, even lacking a book-wide reference section. and the reference section for each chapter doesn't have numbers!

The book is great but the paper quality is very bad for the price. Not worth it.

for NLP practitioners who do not want to skim through the entire internet to look for any concept, this is a very good book as it is concise and good in both theory as well as code