  Both conceptual modeling and machine learning have long been recognized as
important areas of research. With the increasing emphasis on digitizing and
processing large amounts of data for business and other applications, it would
be helpful to consider how these areas of research can complement each other.
To understand how they can be paired, we provide an overview of machine
learning foundations and development cycle. We then examine how conceptual
modeling can be applied to machine learning and propose a framework for
incorporating conceptual modeling into data science projects. The framework is
illustrated by applying it to a healthcare application. For the inverse
pairing, machine learning can impact conceptual modeling through text and rule
mining, as well as knowledge graphs. The pairing of conceptual modeling and
machine learning in this this way should help lay the foundations for future
research.
