Assigning molecular spectra is a necessary evil: we obtain a wealth of information about chemistry and physics through tedious and error-prone manual analysis by searching for patterns and assigning spectral features to transitions between quantum mechanical states. I developed a set of recurrent neural network models with reinforcement learning to “teach” a computer how to solve spectra.