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Transformers for Natural Language Processing

You're reading from   Transformers for Natural Language Processing Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781800565791
Length 384 pages
Edition 1st Edition
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Author (1):
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Denis Rothman Denis Rothman
Author Profile Icon Denis Rothman
Denis Rothman
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started with the Model Architecture of the Transformer 2. Fine-Tuning BERT Models FREE CHAPTER 3. Pretraining a RoBERTa Model from Scratch 4. Downstream NLP Tasks with Transformers 5. Machine Translation with the Transformer 6. Text Generation with OpenAI GPT-2 and GPT-3 Models 7. Applying Transformers to Legal and Financial Documents for AI Text Summarization 8. Matching Tokenizers and Datasets 9. Semantic Role Labeling with BERT-Based Transformers 10. Let Your Data Do the Talking: Story, Questions, and Answers 11. Detecting Customer Emotions to Make Predictions 12. Analyzing Fake News with Transformers 13. Other Books You May Enjoy
14. Index
Appendix: Answers to the Questions

Summary

Fake news begins deep inside our emotional history as humans. When an event occurs, emotions take over to help us react quickly to a situation. We are hardwired to react strongly when we are threatened.

Fake news spurs strong reactions. We fear that this news could temporarily or permanently damage our lives. Many of us believe climate change could eradicate human life from Earth. Others believe that if we react too strongly to climate change, we might destroy our economies and break society down. Some of us believe that guns are dangerous. Others remind us that the Second Amendment of the United States Constitution gives us the right to possess a gun in the US.

We went through other raging conflicts over COVID-19, former President Trump, and climate change. In each case, we saw that emotional reactions are the fastest ones to build up into conflicts.

We then designed a roadmap to take the emotional perception of fake news to a rational level. We used...

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