With the combined power of a CNN and a dense network, textual data and image data can be used to predict home prices.
Houses from an online California dataset along with a set of extracted Toronto homes have been trained upon.
A combination of regular network training and weight sharing via transfer learning from large datasets is used to optimize the model.