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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
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.