This guide takes you through the steps to create an environment for performing selected data science experiments with Microsoft Azure Machine Learning Studio (MLS).

Requirements

To perform the following tasks, you will need the following:

1. A Windows, Linux, or Mac OSX computer.
2. A web browser and Internet connection.
3. Create an Azure ML Account. Azure ML offers a free-tier account, which you can use to complete the experiments. Note that a free Azure ML workspace is not the same as a Microsoft Azure trial subscription. Sign Up for a Microsoft Account and a Free Azure ML Workspace:
   1. If you do not already have a Microsoft account, sign up for one at https://signup.live.com/.
   2. If you do not already have an Azure ML workspace, browse to either http://aka.ms/edx-dat203.1x-aml (click Get Started Now) or http://studio.azureml.net (click Sign Up –> Free Workspace). Then follow the instructions to sign up for a free Azure ML workspace. If prompted, sign in with your Microsoft account credentials. Note that Your free-tier Azure ML workspace allows you unlimited access, with some reduced capabilities compared to a full Microsoft Azure subscription. Your experiments will only run at low priority on a single processor core. As a result, you will experience some longer wait times. However, you have full access to all features of Azure ML.

By completing these tasks, you have prepared you environment for the experiments. Now you’re ready to start learning how to build data science and machine learning solutions with the Microsoft Azure MLS.

References

1. Official documentation of the Machine Learning Studio from Microsoft.
2. Microsoft Professional Program for Data Science track, which is FREE and available online at edX.org.
3. Free eBooks from Microsoft Press