Hitchhikers Guide to Azure Machine Learning Studio

Learn Azure ML Studio through this brief hands-on tutorial. This step-by-step guide will help you get a quick-start and grasp the basics of this Predictive Modeling tool.

Web Service

One of the best feature of Azure Machine Learning Studio is that it provides a building Web Service tutorial which could be access using .NET, Python or R Shiny App.

We are now going to build a web service on the top of our predictive service. It is as simple as eating a cake.

Click on Setup Web service and Deploy Web Service.
You should then see a page like this.
Above mentioned is your API Key which you will use to deploy web service on a third-part. We will explain that later in the tutorial. You can test your web service by clicking on test.

Click on Request/Response and you would see the parameters to use it in a third-party environment. At the end of the page, you’d see the code generated by Azure ML studio.
To make a real-time web application, we would be using Python for this tutorial. You can make use of .NET and R Shiny as per your skills.

You can download the Python based web app, which is made under Django framework via this link.

To view the application running in live mode please click here

Most of the hosting websites don't have support for python. I have hosted the application at my personal AWS instance.

Author Bio:

Usman is an aspiring data scientist. He tweets @rana_usman and can be reached at usmanashrafrana@gmail.com