Keras implementation of Tensorflow's Wide and Deep Algorithm
Keras implementation of Tensorflow's Wide and Deep Algorithm
This is just a quick, fun excercise trying to implement Tensorflow's Wide and Deep Algorithm wide and deep in Keras using the Functional API. Needless to say, if you are ever going to go use Wide and Deep, go for the Tensorflow implementation. Original paper here.
Hi Jrzaurin
Thank you so much for your excellent coding for w&d model.
I know this one you have finished two years ago, but I still want to talk about some details with you.
From the original paper and the official TF implementation, the optimization was done by two optimizers parallel.
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/learn/python/learn/estimators/dnn_linear_combined.py#L328
Do you know how Keras can use two optimizers before concatenated the logits? Or Do you consider two optimizers are unnecessary?
Hey man!
How did your model do on a project/dataset of yours? Thanks!
The URL given in the code is not available, and it is impossible to download the data.
Data download link is not working. Can you please add data here only if its not too big?
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