  The emerging technology of multi-tenancy network slicing is considered as an
essential feature of 5G cellular networks. It provides network slices as a new
type of public cloud services, and therewith increases the service flexibility
and enhances the network resource efficiency. Meanwhile, it raises new
challenges of network resource management. A number of various methods have
been proposed over the recent past years, in which machine learning and
artificial intelligence techniques are widely deployed. In this article, we
provide a survey to existing approaches of network slicing resource management,
with a highlight on the roles played by machine learning in them.
