  We use a supervised machine-learning model based on a neural network to
predict the temporal and spectral intensity profiles of the pulses that form
upon nonlinear propagation in optical fibers with both normal and anomalous
second-order dispersion. We also show that the model is able to retrieve the
parameters of the nonlinear propagation from the pulses observed at the output
of the fiber. Various initial pulse shapes as well as initially chirped pulses
are investigated.
