# Classification and regression on same deep learning models?

Suppose I have a dataset of photos of people's faces. One face per image. What does the output vector for a single sample look like, and how do I train the network if I want it to:

• predict the age (in days) of the person in the image

• classify the person's gender

• classify country of origin (say, out of only 7 possible options)

• predict (x,y) coordinates of person's nose within the picture (where each coordinate is a value between 0-1, indicating percentage of the distance from top left corner of the input image)

This is a strange question. "What does the output vector for a single sample look like?", well, you write the model, so you decide how you chooses to code "the output", which I take to mean $Y$, the response variable that you want to predict. So for your examples:
4. predict (x,y) coordinates of person's nose within the picture (where each coordinate is a value between 0-1, indicating percentage of the distance from top left corner of the input image): Just encode $(x,y)$ in the obvious way, as a pair