I was going through "Wide & Deep Learning" tensorflow tutorial & it's quite simply explained the process. But I missed few of the things. If someone can please explain them to me, it will be of great help:
native_country we are using
tf.feature_column.categorical_column_with_hash_bucket and again using
2) Why in
tf.feature_column.embedding_column, we are taking
dimension=8, even though they have more unique values?
3) Why we are using
crossed_columns variables? In the document there's an explaination given. But I'm not fully understanding it.
The questions might sound silly, but I'm not sure of the answers to these questions.