*Note Special Day
The NOvA experiment is a long-baseline neutrino oscillation experiment that uses two detectors separated by 809 kilometers to measure muon neutrino disappearance and electron neutrino appearance in the beam produced at Fermilab. These oscillation channels are sensitive to unknown parameters in neutrino oscillations including the mass hierarchy, θ23, and CP violation. In this talk I will focus on the development and application of deep learning algorithms to the task of event reconstruction and classification in NOvA. These algorithms, adapted from computer vision applications, resulted in a performance gain equivalent to a 30% increase in exposure in the 2016 analysis. I will also look at future deep learning applications.