PyData Berlin 2018
Understanding attention mechanisms and self-attention, presented in Google’s “Attention is all you need” paper, is a beneficial skill for anyone who works on complex NLP problems. In this talk, we will go over the main parts of the Google Transformer self-attention model and the intuition behind it. Then we will look on how this architecture can be used for other NLP tasks, i.e. slot filling.
Slides: https://www.dropbox.com/s/hri8veio4rep5g4/Self-Attention_for_NLP_by_Ivan_Bilan.pptx?dl=0
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