docker

There are a lot of articles out there explaining how to wrap Flask around your machine learning models to serve them as a RESTful API. This article assumes that you already have wrapped your model in a Flask REST API, and focuses more on getting it production ready using Docker. Motivation Why do we need to further work on our Flask API to make it deployable? Flask’s built-in server is not suitable for production Docker allows for smoother deployments, more reliability, and better developer-production parity than attempting to run Flask on a standard Virtual Machine....