Lecture
Transformer Networks: Self-Attention
Description
This lecture covers Transformer networks and self-attention layers, explaining how they map sets of inputs and the concept of multi-head attention. It delves into the process of learning weights, the importance of positional encoding, and the interpretability of the heads.
Official source
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