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Hands-on Question Answering Systems with BERT - Applications in Neural Networks and Natural Language Processing (Paperback, 1st ed.)
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Hands-on Question Answering Systems with BERT - Applications in Neural Networks and Natural Language Processing (Paperback, 1st ed.)
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Get hands-on knowledge of how BERT (Bidirectional Encoder
Representations from Transformers) can be used to develop question
answering (QA) systems by using natural language processing (NLP)
and deep learning. The book begins with an overview of the
technology landscape behind BERT. It takes you through the basics
of NLP, including natural language understanding with tokenization,
stemming, and lemmatization, and bag of words. Next, you'll look at
neural networks for NLP starting with its variants such as
recurrent neural networks, encoders and decoders, bi-directional
encoders and decoders, and transformer models. Along the way,
you'll cover word embedding and their types along with the basics
of BERT. After this solid foundation, you'll be ready to take a
deep dive into BERT algorithms such as masked language models and
next sentence prediction. You'll see different BERT variations
followed by a hands-on example of a question answering system.
Hands-on Question Answering Systems with BERT is a good starting
point for developers and data scientists who want to develop and
design NLP systems using BERT. It provides step-by-step guidance
for using BERT. What You Will Learn Examine the fundamentals of
word embeddings Apply neural networks and BERT for various NLP
tasks Develop a question-answering system from scratch Train
question-answering systems for your own data Who This Book Is For
AI and machine learning developers and natural language processing
developers.
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