Azure ML: Deploying your model as a Web Service

Deploying a model basically means creating a service out of your model and making it accessible to others.

Today we will see how one can leverage Azure ML platform to deploy a machine learning model as a web service.

The deployment can be done in two ways:

• Using UI (No-Code approach)

• Using Azure's Python SDK (code available on Github)

We take up both the approaches and understand each of them, let’s go! 🚀