Deploying Keras Deep Learning Models with Flask – Towards Data Science

This post demonstrates how to set up an endpoint to serve predictions using a deep learning model built with Keras. It first introduces an example using Flask to set up an endpoint with Python, and then shows some of issues to work around when building a Keras endpoint for predictions with Flask. The goal of this post is to show how to set up a Keras model as an endpoint on an EC2 instance with AWS. Some of the issues that I'll cover include handling a custom metric when using model persistence with Keras, dealing with multi-threading concerns when using Keras in combination with Flask, and getting it all running on an EC2 instance. The complete code listing for this post is available on GitHub.