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...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Sabharwal, Navin, Agrawal, Amit
Format: E-Book Buch
Sprache:Englisch
Veröffentlicht: Berkeley, CA Apress, an imprint of Springer Nature 2021
Apress
Apress L. P
Ausgabe:1
Schlagworte:
Automatic control
Computer Science
Data processing
General References
Machine Learning
MATHEMATICS
Neural networks (Computer science)
Pattern recognition systems
Professional and Applied Computing
Professional Computing
Software Engineering
ISBN:1484266633, 9781484266632, 9781484266649, 1484266641
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:Includes index
ISBN:1484266633
9781484266632
9781484266649
1484266641
DOI:10.1007/978-1-4842-6664-9