Has anyone tried to reduce the dimensions of one of the embedding layers from a tabular model to visualise it?
I’m thinking along the lines of https://projector.tensorflow.org/ (in particular I like T-SNE) where instead of words as labels for each point you instead use features e.g. gender, product name etc.
@Pak did some work with this. See the end of his notebook where he visualized the distances of the embeddings
Thanks @muellerzr you’re a super helpful guy! I’ve had a very quick look and couldn’t figure out how to interpret them, but I’ll have a gander at the source code and see if I can figure it out.