Back to Module 1.10: TransformersIn Progress
AI Lesson & Submodule
Attention + Residual Connection
Understand how skip connections preserve gradient flows.
Why This Matters
Residual connections bypass layers directly, preventing gradients from shrinking to zero during backpropagation.
What You Will Learn
- •Explain skip connections
- •Prevent gradient vanishing
- •Verify vector addition shapes
Concepts Covered
Skip connections logicVanishing gradients preventionTensor addition dimensions
Mapped Foundation Project: Mini Transformer Block Explainer
Visual deconstruction of a standard decoder block, outlining normalizations, skip links, and output projections.
Architecture Preview
Block-by-block diagram tracking vector changes as inputs pass through decoder normalizations and linear mappings.
Input TokensLayer Norm Layer 1Multi-Head Attention Block
Tech Stack Planned
ReactTypeScriptFramer Motion
GitHub: Coming SoonLive Demo: Coming Soon
Coming SoonTechnical Interview Value
- ?Explain why residual skip connections are mathematically required to train very deep neural networks