  We present results from the fastsum collaboration's programme to determine
the spectrum of the bottomonium system as a function of temperature. Three
different methods of extracting spectral information are discussed: a Maximum
Likelihood approach using a Gaussian spectral function for the ground state,
the Backus Gilbert method, and the Kernel Ridge Regression machine learning
procedure. We employ the fastsum anisotropic lattices with 2+1 dynamical quark
flavours, with temperatures ranging from 47 to 375 MeV.
