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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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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

Further reading

For more information, refer to the following resources:

  • Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks by Nils Reimers and Iryna Gurevych, available at https://arxiv.org/pdf/1908.10084.pdf
  • Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation by Nils Reimers and Iryna Gurevych, available at https://arxiv.org/pdf/2004.09813.pdf
  • ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission by Kexin Huang, Jaan Altosaar, and Rajesh Ranganath, available at https://arxiv.org/pdf/1904.05342.pdf
  • BioBERT: a pre-trained biomedical language representation model for biomedical text mining by Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang, available at https://arxiv.org/pdf/1901.08746.pdf
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