  We deploy a supervised machine-learning model based on a neural network to
predict the temporal and spectral reshaping of a simple sinusoidal modulation
into a pulse train having a comb structure in the frequency domain, which
occurs upon nonlinear propagation in an optical fibre. Both normal and
anomalous second-order dispersion regimes of the fibre are studied, and the
speed of the neural network is leveraged to probe the space of input parameters
for the generation of custom combs or the occurrence of significant temporal or
spectral focusing.
