Hi Team!!
My autoencoder model has numerical, categorical and text features. I am doing a normalization for numerical, custom encoding for categorical and BERT tokenization for text as preprocessing.
I want to build a preprocessing layer with different custom preprocessing for each feature. All the examples on documentation (e.g. Keras Preprocessing Layers - YouTube) I see is for uniform attributes like full text or numerical dataset.
Please help me on this.