  Methods based on machine learning have recently made substantial inroads in
many corners of cosmology. Through this process, new computational tools, new
perspectives on data collection, model development, analysis, and discovery, as
well as new communities and educational pathways have emerged. Despite rapid
progress, substantial potential at the intersection of cosmology and machine
learning remains untapped. In this white paper, we summarize current and
ongoing developments relating to the application of machine learning within
cosmology and provide a set of recommendations aimed at maximizing the
scientific impact of these burgeoning tools over the coming decade through both
technical development as well as the fostering of emerging communities.

High Energy Physics - Phenomenology;Cosmology and Nongalactic Astrophysics;Instrumentation and Methods for Astrophysics;Machine Learning;Machine Learning