R u aware of any colab notebook that demo how to deal with field that r multi-value and categorical (high cardinality). e.g. favorite_topics whose values (politics, sport, etc) where 1 or more values can be picked. I am trying to think how to do this with entity embedding.
Here's regression example on the Ames Housing Price dataset. This dataset turns out to be great for demonstrating how to vectorize structured data, and how to handle missing features. https://colab.research.google.com/drive/127UxEcvp9KKrf2rNGlHBfyUMgcoQE0zi …
Thanks to @micahjsmith for suggesting this dataset!
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Thanks a lot for this. Didn’t know about wide and deep network. But i don’t get the vectorization step here what is the wisdom behind doing it “manually” like in the notebook and just use pandas dummies then delete the non frequent column and then call values on the datafram. Thx
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Thanks for sharing, comes v handy for me, as I am taking TensorFlow sessions in my org rt now :)
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