By now, we know how to create a deep learning model for various tasks. It accepts/returns tensors as input/output. But an outsider such as a client/end user would talk only in terms of images and classes. Furthermore, they would expect to send and receive input/output over channels that might have nothing to do with Python. The internet is the easiest channel to communicate on. Hence, for a client, the best-case deployment scenario would be if we can set up a publically available URL and ask them to upload their images there. One such paradigm is called an Application Programming Interface (API), which has standard protocols that accept input and post output over the internet while abstracting the user away from how the input is processed or the output is generated.
Some common protocols in APIs are POST, GET, PUT, and DELETE, which are sent as requests by the client to the host server along with relevant data. Based on the request and data, the server...
