  We present the first version of the ALeRCE (Automatic Learning for the Rapid
Classification of Events) broker light curve classifier. ALeRCE is currently
processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for
the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses
variability features computed from the ZTF alert stream, and colors obtained
from AllWISE and ZTF photometry. We apply a Balanced Random Forest algorithm
with a two-level scheme, where the top level classifies each source as
periodic, stochastic, or transient, and the bottom level further resolves each
of these hierarchical classes, amongst 15 total classes. This classifier
corresponds to the first attempt to classify multiple classes of stochastic
variables (including core- and host-dominated active galactic nuclei, blazars,
young stellar objects, and cataclysmic variables) in addition to different
classes of periodic and transient sources, using real data. We created a
labeled set using various public catalogs (such as the Catalina Surveys and
{\em Gaia} DR2 variable stars catalogs, and the Million Quasars catalog), and
we classify all objects with $\geq6$ $g$-band or $\geq6$ $r$-band detections in
ZTF (868,371 sources as of 2020/06/09), providing updated classifications for
sources with new alerts every day. For the top level we obtain macro-averaged
precision and recall scores of 0.96 and 0.99, respectively, and for the bottom
level we obtain macro-averaged precision and recall scores of 0.57 and 0.76,
respectively. Updated classifications from the light curve classifier can be
found at the \href{http://alerce.online}{ALeRCE Explorer website}.
