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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

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781838821593
Length 352 pages
Edition 1st Edition
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Author (1):
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Sudharsan Ravichandiran Sudharsan Ravichandiran
Author Profile Icon Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Toc

Table of Contents (15) Chapters Close

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

Questions

Let's put our newly acquired knowledge to the test. Try answering the following questions:

  1. What are the steps involved in the self-attention mechanism?
  2. What is scaled dot product attention?
  3. How do we create the query, key, and value matrices?
  4. Why do we need positional encoding?
  5. What are the sublayers of the decoder?
  6. What are the inputs to the encoder-decoder attention layer of the decoder?
You have been reading a chapter from
Getting Started with Google BERT
Published in: Jan 2021
Publisher: Packt
ISBN-13: 9781838821593
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