  Interferometric measurements of the 21cm signal are a prime example of the
data-driven era in astrophysics we are entering with current and upcoming
experiments. We showcase the use of deep networks that are tailored for the
structure of 3D tomographic 21cm light-cones to firstly detect and characterise
HI sources and to secondly directly infer global astrophysical and cosmological
model parameters. We compare different architectures and highlight how 3D CNN
architectures that mirror the data structure are the best-performing model.
