This repo has code for a basic example of setting up an API endpoint for calling predictions from a pre-built random forest ML model using Flask, Docker and AWS.
It uses the boston housing dataset from Sci-kit Learn as data for the model.
The goal is to help people put their machine learning models into a production environment where predictions can be made on the fly with new data
Tutorial that I followed to set this up is here.