  Machine learning (ML) technologies are emerging in the Internet of Things
(IoT) to provision intelligent services. This survey moves beyond existing ML
algorithms and cloud-driven design to investigate the less-explored systems,
scaling and socio-technical aspects for consolidating ML and IoT. It covers the
latest developments (up to 2020) on scaling and distributing ML across cloud,
edge, and IoT devices. With a multi-layered framework to classify and
illuminate system design choices, this survey exposes fundamental concerns of
developing and deploying ML systems in the rising cloud-edge-device continuum
in terms of functionality, stakeholder alignment and trustworthiness.
