Transformer Architecture: The X Gomega

This lecture covers the Transformer architecture, focusing on the encoder and decoder components, self-attention mechanism, multi-head attention, positional encodings, and additional operations like residual connections and layer normalization. It explains how Transformers are used for machine translation and image recognition, emphasizing the importance of attention mechanisms and training strategies.