Submitted by Leopiney t3_yk4xnl in deeplearning
SameerMohair t1_iut070w wrote
How does this work when you have embeddings on a vector space of many many dimensions, like google’s name2vec.
Leopiney OP t1_iuup3jm wrote
Hi there! Great question.
In these examples it happens exactly the same, the embeddings have large dimensionalities. What we show is a 2D projection of the embeddings so that we can plot them, regardless of the dimension of the embeddings.
You can choose between UMAP or PCA projections by default.
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