Serving a Machine Learning Model Via REST API

For us to build our API, we are going to leverage the Flask micro-framework. Due to various reasons such as being extremely powerful, simple to use, and very good documentation, Flask is a popular choice for microservices in Python -- See Documentation. "Micro" does not mean that your whole web application has to fit into a single Python file (although it certainly can), nor does it mean that Flask is lacking in functionality. The "micro" in microframework means Flask aims to keep the core simple but extensible. Let's first take a look at our directory structure… The topmost directory is ml_api and within this directory there is requirements.txt