  Improving our knowledge of global Milky Way (MW) properties is critical for
connecting the detailed measurements only possible from within our Galaxy to
our understanding of the broader galaxy population. We train Gaussian Process
Regression (GPR) models on SDSS galaxies to map from galaxy properties (stellar
mass, apparent axis ratio, star formation rate, bulge-to-total ratio, disk
scale length, and bar vote fraction) to UV (GALEX $FUV/NUV$), optical (SDSS
$ugriz$) and IR (2MASS $JHKs$ and WISE $W1/W2/W3/W4$) fluxes and uncertainties.
With these models we estimate the photometric properties of the MW, resulting
in a full UV-to-IR spectral energy distribution (SED) as it would be measured
externally, viewed face-on. We confirm that the Milky Way lies in the green
valley in optical diagnostic diagrams, but show for the first time that the MW
is in the star-forming region in standard UV and IR diagnostics --
characteristic of the population of red spiral galaxies. Although our GPR
method predicts one band at a time, the resulting MW UV--IR SED is consistent
with SEDs of local spirals with characteristics broadly similar to the MW,
suggesting that these independent predictions can be combined reliably. Our
UV--IR SED will be invaluable for reconstructing the MW's star formation
history using the same tools employed for external galaxies, allowing
comparisons of results from \textit{in situ} measurements to those from the
methods used for extra-galactic objects.
