My research group at UCSC is running very high resolution hydrodynamic simulations of galaxy formation and evolution for comparison with the galaxy images from the CANDELS survey (http://candels.ucolick.org/About.html), the largest project in the history of Hubble Space Telescope (HST). We are using visualizations of the evolution of gas and stars to help us understand the key processes in the simulations. We are also using our state-or-the-art Sunrise radiative transfer code to make realistic images from the simulations in many wavebands, including the effects of stellar evolution and dust scattering, absorption, and re-emission. We are using automatic neural net machine learning to classify these images and those from CANDELS (using thousands of CANDELS images that have been classified by astronomers as a training set), in order to see the extent to which the simulations agree with the HST observations.