Hands-on question answering systems with BERT : applications in neural networks and natural language processing

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 thr...

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Bibliographic Details
Main Authors: Sabharwal, Navin, (Author), Agrawal, Amit, (Author)
Format: eBook
Language: English
Published: [Berkeley, California] : Apress, [2021]
Subjects:
Neural networks (Computer science)
Machine learning.
Natural language processing (Computer science)
elektronické knihy
electronic books
ISBN: 9781484266649
1484266641
1484266633
9781484266632
9781484266656
148426665X
Physical Description: 1 online resource : illustrations

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Table of contents

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003 OCoLC
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006 m o d
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008 210222s2021 caua ob 001 0 eng d
040 |a N$T  |b eng  |e rda  |e pn  |c N$T  |d N$T  |d OCLCO  |d GW5XE  |d SFB  |d OCLCF  |d VT2  |d EBLCP  |d YDX  |d LDP  |d ERF  |d DCT  |d UKAHL  |d OCL  |d OCLCQ  |d OCLCO  |d COM  |d OCLCQ  |d OCLCO  |d OCLCL  |d HOPLA 
020 |a 9781484266649  |q (electronic bk.) 
020 |a 1484266641  |q (electronic bk.) 
020 |a 1484266633 
020 |a 9781484266632 
020 |a 9781484266656  |q (print) 
020 |a 148426665X 
020 |z 9781484266632 
024 7 |a 10.1007/978-1-4842-6664-9  |2 doi 
035 |a (OCoLC)1238031485  |z (OCoLC)1231522303  |z (OCoLC)1231610934  |z (OCoLC)1236311999  |z (OCoLC)1238202415  |z (OCoLC)1238203968  |z (OCoLC)1238205343  |z (OCoLC)1240510405 
100 1 |a Sabharwal, Navin,  |e author. 
245 1 0 |a Hands-on question answering systems with BERT :  |b applications in neural networks and natural language processing /  |c Navin Sabharwal and Amit Agrawal. 
264 1 |a [Berkeley, California] :  |b Apress,  |c [2021] 
300 |a 1 online resource :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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. You will: 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. 
505 0 |a Introduction to Natural Language Processing -- Neural Networks for Natural Language Processing -- Introduction to Word Embeddings -- BERT Algorithms Explained -- BERT Model Applications : Question Answering System -- BERT Model Applications : Other tasks -- Future of BERT models. 
504 |a Includes bibliographical references and index. 
590 |a Knovel  |b Knovel (All titles) 
650 0 |a Neural networks (Computer science) 
650 0 |a Machine learning. 
650 0 |a Natural language processing (Computer science) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 1 |a Agrawal, Amit,  |e author. 
776 0 |z 1484266633 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpHQASBER2/hands-on-question?kpromoter=marc  |y Full text 

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