Machine learning can be hard but moving your ML model to your embedded device can be even harder.

This article by John Fogart discusss a few pain points in this process, and some solutions.

How do you get from this set of tools, code and data using many different formats, sources, licenses and execution environments into something that you can execute entirely inside some little box—one that may (or may not) be connected to the internet ever again?

ExplainingComputers explores Edge computing definitions and concepts.

This non-technical video focuses on edge computing and cloud computing, as well as edge computing and the deployment of vision recognition and other AI applications.

Also introduced are mesh networks, SBC (single board computer) edge hardware, and fog computing.