  In this paper we show how using satellite images can improve the accuracy of
housing price estimation models. Using Los Angeles County's property assessment
dataset, by transferring learning from an Inception-v3 model pretrained on
ImageNet, we could achieve an improvement of ~10% in R-squared score compared
to two baseline models that only use non-image features of the house.
