So I have three types of data (in title) and am wondering how I can combine the data. The target is numeric (price).
My idea is to perform feature extraction on both the images and text, which would result in a 1 dim row vector of size n. So this would produce n features. After this, combine all the data and normalize. The model would be trained on this combined dataset.
I have really only worked with one data type or the other, so I am unsure if this is the right approach. I haven't found many relevant resources for this type of problem, but let me know if I am missing something.