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SHIVANI SHAH, congratulations on completing Attention in Transformers: Concepts and Code in PyTorch!

Attention in Transformers: Concepts and Code in PyTorch
Short Course

Attention in Transformers: Concepts and Code in PyTorch

Understand and implement the attention mechanism, a key element of transformer-based LLMs, using PyTorch.

Deep LearningEmbeddingsGenAI ApplicationsMachine LearningNLPTransformers
  • StatQuest
StatQuest
100% Completed
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  • Introduction
    Video
    ・
    6 mins
  • The Main Ideas Behind Transformers and Attention
    Video
    ・
    4 mins
  • The Matrix Math for Calculating Self-Attention
    Video
    ・
    11 mins
  • Coding Self-Attention in PyTorch
    Video with Code Example
    ・
    8 mins
  • Self-Attention vs Masked Self-Attention
    Video
    ・
    14 mins
  • The Matrix Math for Calculating Masked Self-Attention
    Video
    ・
    3 mins
  • Coding Masked Self-Attention in PyTorch
    Video with Code Example
    ・
    5 mins
  • Encoder-Decoder Attention
    Video
    ・
    4 mins
  • Multi-Head Attention
    Video
    ・
    2 mins
  • Coding Encoder-Decoder Attention and Multi-Head Attention in PyTorch
    Video with Code Example
    ・
    4 mins
  • Conclusion
    Video
    ・
    1 min
  • Appendix – Tips and Help
    Code Example
    ・
    1 min