Given a shallow or deep neural network, how would one go about using both continuous numerical input features and categorical features?
For example, given a network that receives a set of 100 continuous numerical values between 0 and 1 representing monetary value, how would I also include a time component? I would suspect one would have to discretize/translate intraday hours and minutes, e.g. 21:35 into bins of say 1 hour. This would yield a one-hot vector that I would then append to my input data that flows into the network. Would this be a valid approach?