The deployment and maintenance of AI applications is more than just a single action; it's a process. In this section, we will work through creating sustainable applications in the cloud by creating a deep learning deployment architecture. These architectures will help us create end-to-end systems: deep learning systems.
In many machine learning/AI applications, the typical project pipeline and workflow might look something like the following:
The training processes are strictly offline, and serialized models are pushed to the cloud and interact with a user through an API. These processes often leave us with several different ...
