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Getting Started with Google BERT
Getting Started with Google BERT

Getting Started with Google BERT: Build and train state-of-the-art natural language processing models using BERT

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Profile Icon Sudharsan Ravichandiran
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2 (50 Ratings)
Paperback Jan 2021 352 pages 1st Edition
eBook
$29.99
Paperback
$43.99
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Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Sudharsan Ravichandiran
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2 (50 Ratings)
Paperback Jan 2021 352 pages 1st Edition
eBook
$29.99
Paperback
$43.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$29.99
Paperback
$43.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Explore the encoder and decoder of the transformer model
  • Become well-versed with BERT along with ALBERT, RoBERTa, and DistilBERT
  • Discover how to pre-train and fine-tune BERT models for several NLP tasks

Description

BERT (bidirectional encoder representations from transformer) has revolutionized the world of natural language processing (NLP) with promising results. This book is an introductory guide that will help you get to grips with Google's BERT architecture. With a detailed explanation of the transformer architecture, this book will help you understand how the transformer’s encoder and decoder work. You’ll explore the BERT architecture by learning how the BERT model is pre-trained and how to use pre-trained BERT for downstream tasks by fine-tuning it for NLP tasks such as sentiment analysis and text summarization with the Hugging Face transformers library. As you advance, you’ll learn about different variants of BERT such as ALBERT, RoBERTa, and ELECTRA, and look at SpanBERT, which is used for NLP tasks like question answering. You'll also cover simpler and faster BERT variants based on knowledge distillation such as DistilBERT and TinyBERT. The book takes you through MBERT, XLM, and XLM-R in detail and then introduces you to sentence-BERT, which is used for obtaining sentence representation. Finally, you'll discover domain-specific BERT models such as BioBERT and ClinicalBERT, and discover an interesting variant called VideoBERT. By the end of this BERT book, you’ll be well-versed with using BERT and its variants for performing practical NLP tasks.

Who is this book for?

This book is for NLP professionals and data scientists looking to simplify NLP tasks to enable efficient language understanding using BERT. A basic understanding of NLP concepts and deep learning is required to get the best out of this book.

What you will learn

  • Understand the transformer model from the ground up
  • Find out how BERT works and pre-train it using masked language model (MLM) and next sentence prediction (NSP) tasks
  • Get hands-on with BERT by learning to generate contextual word and sentence embeddings
  • Fine-tune BERT for downstream tasks
  • Get to grips with ALBERT, RoBERTa, ELECTRA, and SpanBERT models
  • Get the hang of the BERT models based on knowledge distillation
  • Understand cross-lingual models such as XLM and XLM-R
  • Explore Sentence-BERT, VideoBERT, and BART

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 22, 2021
Length: 352 pages
Edition : 1st
Language : English
ISBN-13 : 9781838821593
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Google
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Product Details

Publication date : Jan 22, 2021
Length: 352 pages
Edition : 1st
Language : English
ISBN-13 : 9781838821593
Vendor :
Google
Category :
Languages :
Tools :

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Frequently bought together


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Total $ 198.97
Transformers for Natural Language Processing
$99.99
Mastering Transformers
$54.99
Getting Started with Google BERT
$43.99
Total $ 198.97 Stars icon
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Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.2
(50 Ratings)
5 star 72%
4 star 4%
3 star 6%
2 star 8%
1 star 10%
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Ashwini Mar 05, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I liked this book about BERT. This is one of the great books on BERT that I have come across. The author takes detailed accounts of introduction and applications of BERT before explaining things in detail. I loved the fact that there are frameworks explaining how each and every topic works in BERT. The book is a bit mathy but great for people who want to understand things in details.
Amazon Verified review Amazon
Xan Jan 11, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
First of all let me start by saying I am working as an NLP Data Scientist for some years now and my work especially involves using transformers models. Even though people are right about the print of the book the content is invaluable. I really haven’t found another book explaining in such details the transformers models until now. Transformers are the state of the art in NLP so someone should already be comfortable with general NLP to get value out of the book. Kudos to the authors for their writing style which I found entertaining. I hope they will create another version with newest developments and use better printing (maybe partner with o Reilly?). So, for data scientist working currently with transformers this is a very good addition to their library.
Amazon Verified review Amazon
Kai Apr 23, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I used this book to learn more about applying Google's BERT in my day-to-day job and Sudharsan does an excellent job to present the topics to the audience in a concise and clear manner, along with quality examples that are easy to follow along.I will not hesitate to recommend this to my peers who are getting into the industry.
Amazon Verified review Amazon
Alec Feb 18, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The attention mechanism is hard to learn, the explanatory chapter in this book makes it easier by explaining it showing some vector transformations and matrix multiplication, not just diagrams (as is usual). Nowhere does he say "it works by paying attention", or "it attends over the input", which bolsters my sanity.There are many code examples for all the networks talked about (RoBERTa, DistilBERT, ELECTRA), and a lot of the additional capabilities of BERT are expanded on, like using BERT for question answering. Altogether, it's very comprehensive, and a good source for someone who wants to get started with transformers and wants one source that will tell them what they need to know.
Amazon Verified review Amazon
Emanuel Di Nardo Feb 15, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I found this book to be really enjoyable. The author uses a conversational tone and this helps a lot when you try to understand complex neural network models.It begins with an introduction on transformer models: you'll learn about encoders-decoders architectures, seq2seq models with LSTMs & GRUs and all this is wonderfully explained in this book.It feels like the author wrote this book to make people learn and enjoy the topic, rather than just show his math skills as done in some books/papers.The author also introduces several use-cases for Google's BERT architecture: Bert in other languages, VideoBERT, BART and so on.This book is a good one for you if you're looking for a book that helps you understand NLP, BERT architecture with examples and some use-cases in which this kind of model can be applied.
Amazon Verified review Amazon
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