Prepare Week 5 Lecture Note: Introduction to Transformer Architecture

[entelecheia]

Objective

Create a comprehensive lecture note for Week 5 of the intronlp-2024 course, focusing on the Introduction to Transformer Architecture.

Content to Include

1. Overview of Transformer Architecture

   • Brief history and context
   • Importance in modern NLP

2. Attention Mechanism

   • Concept and intuition behind attention
   • Types of attention (self-attention, multi-head attention)
   • Mathematical formulation of attention

3. Transformer Structure

   • Encoder-decoder architecture
   • Key components: embedding layers, positional encoding, feed-forward networks
   • Detailed explanation of each layer's function

4. Analysis of Transformer Model Structure

   • Step-by-step walkthrough of information flow in a transformer
   • Visualization of attention patterns
   • Comparison with previous architectures (RNNs, LSTMs)

5. Practical Examples

   • Code snippets demonstrating key concepts
   • Visualization of transformer components

6. Discussion Points

   • Advantages and limitations of transformers
   • Impact on various NLP tasks

Deliverables

• Markdown file with lecture content
• Accompanying Jupyter notebook with code examples and visualizations