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Название: Hands-on Question Answering Systems with BERT: Applications in Neural Networks and Natural Language Processing
Автор: Navin Sabharwal, Amit Agrawal
Издательство: Apress
Год: 2021
Страниц: 192
Язык: английский
Формат: pdf (true), epub
Размер: 11.1 MB
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.
Автор: Navin Sabharwal, Amit Agrawal
Издательство: Apress
Год: 2021
Страниц: 192
Язык: английский
Формат: pdf (true), epub
Размер: 11.1 MB
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.