Simple Way To Deploy Ml Models As Flask Apis On Amazon Ecs

This article provides an overview of the process of deploying a trained XGBoost ML model to production. It covers the steps of creating a separate Python 3.8 environment, building an API which can serve the model’s predictions, and running the API locally. Lastly, it explains the process of dockerizing the API and deploying it to Amazon ECS.