Greetings one and all,

I am beginning to learn Mathematica for purposes of machine learning (had some basic experience using Tensorflow previously). I understand that the Predict() function is a high level tool for generating a regression-like prediction using a specified method.

I have a couple of questions if someone could help me clarify:

1) Are different input types handled automatically? By this I mean, could I simply feed numerical and categorical variables to the Predict() function? Previously, I had to perform one-hot encoding for categorical variables, and I noticed Mathematica has the NetEncoder() function. Is it mandatory here? In a video (https://www.youtube.com/watch?v=lczqhcnVQ8c) around the 27:00 mark, it states that Mathematica are trying to develop multiple output types, but what about inputs?

2) Do I need to normalize the variables?

3) I am assuming that in the Predict() function, if the Neural Network method is specified, it is only a shallow network. What is the approach for me to follow in Mathematica to build a deep learning network?

Thank you and have a great day. Looking forward to hearing your advices.

Regards Ben