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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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Questions

Let's assess our knowledge by answering the following questions:

Define Sentence-BERT.
What is the difference between max pooling and mean pooling?
What is ClinicalBERT?
What is the use of ClinicalBERT?
What is the dataset used for training ClinicalBERT?
How is the probability of re-admission computed using ClinicalBERT?
What is the dataset used for training BioBERT?

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Authors (1)

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.

See other products by Sudharsan Ravichandiran