Transformers + Attention (Masterclass)

Struggling with the mathematics or dimensions of modern neural networks? If you get tripped up by query-key-value dimensions, positional encodings, or scaling factors, this session is built for you.

Many professionals can call .from_pretrained(), but very few can confidently map out the exact matrix transformations happening under the hood.

What we can decode in this session:

1. The Attention Mechanism: Step-by-step breakdown of Scaled Dot-Product and Multi-Head Attention—why it works and how the math scales.
2. Dimensional Math Demystified: Line-by-line tracing of tensor shapes across linear projections, attention heads, and feed-forward layers.
3. Architecture Evolution: How the classic encoder-decoder structure evolved into modern decoder-only LLM architectures.
4. Practical System Alignment: Best practices for setting up model evaluation strategies, fine-tuning configurations, and custom guardrails for production.

How it works:

1. 60-Minute Live Whiteboard Session: A highly interactive, visual deep dive where we map out the math and matrix operations together.
2. The Breakthrough: Walk away with intuitive clarity, completely stripping away the complexity of the equations.