  A business's online, photographic representation can play a crucial role in
its success or failure. We use Yelp's image dataset and star-based review
system as a measurement of an image's effectiveness in promoting a business.
After preprocessing the Yelp dataset, we use transfer learning to train a
classifier which accepts Yelp images and predicts star-ratings. Additionally,
we then train a GAN to qualitatively investigate the common properties of
highly effective images. We achieve 90-98% accuracy in classifying simplified
star ratings for various image categories and observe that images containing
blue skies, open surroundings, and many windows are correlated with higher Yelp
reviews.
