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Data Transform Process
Transform the table schema to be wide (aka. one table column is one feature) if the original table schema is not. We implement it using a batch processing job such as a MaxCompute job.
Calculate the statistical value for the following transform code_gen.
We can use keras layer + feature column to do the data transformation. Please look at the Google Cloud Sample.
Build the common transform function set using TensorFlow. It can be fed into tf.keras.layers.Lambda or normalizer_fn
of numeric_column.
As the transform function set is built upon TensorFlow op, we can ensure the consistency between training and inference.
Transform Work: tf.keras.layers.Lambda Multiple Column Transform: tf.keras.layers.Lambda Feature Column: Categorical Mapper Embedding: Dense Embedding Layer or embedding_column?