  We report the discovery and analysis of 36 new eclipsing EL CVn-type
binaries, consisting of a core helium-composition pre-white dwarf and an
early-type main-sequence companion, more than doubling the known population of
these systems. We have used supervised machine learning methods to search 0.8
million lightcurves from the Palomar Transient Factory, combined with SDSS,
Pan-STARRS and 2MASS colours. The new systems range in orbital periods from
0.46-3.8 d and in apparent brightness from ~14-16 mag in the PTF $R$ or
$g^{\prime}$ filters. For twelve of the systems, we obtained radial velocity
curves with the Intermediate Dispersion Spectrograph at the Isaac Newton
Telescope. We modelled the lightcurves, radial velocity curves and spectral
energy distributions to determine the system parameters. The radii (0.3-0.7
$\mathrm{R_{\odot}}$) and effective temperatures (8000-17000 K) of the
pre-He-WDs are consistent with stellar evolution models, but the masses
(0.12-0.28 $\mathrm{M_{\odot}}$) show more variance than models predicted. This
study shows that using machine learning techniques on large synoptic survey
data is a powerful way to discover substantial samples of binary systems in
short-lived evolutionary stages.
