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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.

By Rana Usman

A lot of people are unfamiliar with one of the best Predictive Modeling tools of Microsoft. It's called Azure Machine Learning Studio.

I am going to give a basic hands-on tutorial with Azure ML studio and build is a censor income predictor. We will be using classification technique to predict top income of a sample dataset already in Azure Machine Learning Studio.

Tutorial outline:
  • How to transform data in Azure ML
  • How to make a predictive model
  • How to make a web service
  • How to consume the web service

Data Transformation

Let's go step by step.
  • Make a free account at https://studio.azureml.net. The trial free version gives you enough space for experimentation.
  • Go to New Experiment and you'd see your work space as following

This is how your work space would look like. At the left are the modules that you would be using to transform, build, the data.

I wouldn't go in technical details. I will keep the tutorial as simple as possible.

At the top right, you can see Saved Data sets. Click on it and you will see two drop downs.
  1. Saved Datasets
  2. Samples

Saved Datasets are the datasets that you will upload to your Workspace. They would be available to use at any instance over a click. The Samples are the datasets that come up with Azure Machine Learning Studio in Default.

Let’s drag and drop the Adult Income Data to the workspace. The first thing we would do is visualizing the dataset. It is the most important step before doing any transformation because unless we don’t know what’s in the data, we would be hitting in the air.
Right click the module and click Visualize and you should see a result like this.
You can click on each variable/column to see the histograms at the right hand side. You would also come across descriptive statistics as follow.
These statistics can give you a quick peek into your data.

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