Learn about using transformers in natural language processing with TensorFlow.
Overview
Syllabus
Introduction
- Why TensorFlow?
- What you should know
- What is TensorFlow?
- What is NLP?
- Transformers, their use, and history
- Transformers for NLP
- Challenge: NLP model size
- Solution: NLP model size
- Bias in BERT and GPT
- How was BERT trained?
- Transfer learning
- Transformer: Architecture overview
- BERT model and tokenization
- Tokenizers
- Self-attention
- Multi-head attention and feedforward network
- Fine-tuning BERT
- Next steps
Taught by
Jonathan Fernandes
