Summary: Basics of Transformers

Get a quick recap of what we covered this chapter.

The Fourth Industrial Revolution, or Industry 4.0, has forced artificial intelligence to make profound evolutions. The Third Industrial Revolution was digital. Industry 4.0 is built on top of the digital revolution, connecting everything to everything, everywhere. Automated processes are replacing human decisions in critical areas, including NLP.

RNNs had limitations that slowed the progression of automated NLP tasks required in a fast-moving world. Transformers filled the gap. A corporation needs summarization, translation, and a wide range of NLP tools to meet the challenges of Industry 4.0.

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Course Introduction

Basics of Transformers

Architecture of the Transformer Model

Fine-Tuning BERT Models

Pretraining a RoBERTa Model from Scratch

Downstream NLP Tasks with Transformers

Machine Translation with the Transformer

The Rise of Transformers with GPT-3 Engines

Applying Transformers for AI Text Summarization

Matching Tokenizers and Datasets

Transformers for NLP—Exam 1

Semantic Role Labeling with BERT-Based Transformers

Your Data Speaks: Story, Questions, and Answers

Detecting Customer Emotions to Make Predictions

Analyzing Fake News with Transformers

Interpreting Black Box Transformer Models

From NLP to Task-Agnostic Transfomer Models

The Emergence of Transformer-Driven Copilots

Transformers for NLP—Exam 2

Conclusion

Appendix

Summary: Basics of Transformers