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Getting Started with Google BERT

You're reading from Getting Started with Google BERT Build and train state-of-the-art natural language processing models using BERT

Product type Paperback

Published in Jan 2021

Publisher Packt

ISBN-13 9781838821593

Length 352 pages

Edition 1st Edition

Languages

Python

Tools

BERT

Concepts

Mobile Application Development

Author (1):

Sudharsan Ravichandiran

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1 - Starting Off with BERT

2. A Primer on Transformers FREE CHAPTER

3. Understanding the BERT Model

4. Getting Hands-On with BERT

5. Section 2 - Exploring BERT Variants

6. BERT Variants I - ALBERT, RoBERTa, ELECTRA, and SpanBERT

7. BERT Variants II - Based on Knowledge Distillation

8. Section 3 - Applications of BERT

9. Exploring BERTSUM for Text Summarization

10. Applying BERT to Other Languages

11. Exploring Sentence and Domain-Specific BERT

12. Working with VideoBERT, BART, and More

13. Assessments

14. Other Books You May Enjoy

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Text summarization

Text summarization is the process of converting a long text into its summary. Suppose we have a Wikipedia article and say we don't want to read the whole article – we just need an overview of the article. In this case, summarizing the Wikipedia article will help us get an overview of the article. Text summarization is widely used for a variety of applications, from summarizing long documents, news articles, blog posts, ranging to many more. In the text summarization task, given a long text, our goal is to convert the given long text into its summary as shown in the figure:

Figure 6.1 – Text summarization

Text summarization is of two types:

Extractive summarization
Abstractive summarization

Now let's explore extractive and abstractive summarization in detail.

Extractive summarization

In extractive summarization, we create a summary from a given text by extracting only the important sentences.

That is, say we are given a long document containing...

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Authors (1)

Sudharsan Ravichandiran

Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.

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