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Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
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Getting Started with Google BERT - Build and train state-of-the-art natural language processing models using BERT (Paperback)
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Getting Started with Google BERT - Build and train state-of-the-art natural language processing models using BERT (Paperback)
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Kickstart your NLP journey by exploring BERT and its variants such
as ALBERT, RoBERTa, DistilBERT, VideoBERT, and more with Hugging
Face's transformers library Key Features 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 Book DescriptionBERT
(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. 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 Who this book is forThis 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.
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