Walkthrough Step 1: Create a Machine Learning workspace

This is the first step of the walkthrough, Develop a predictive analytics solution in Azure Machine Learning.

  1. Create a Machine Learning workspace
  2. Upload existing data
  3. Create a new experiment
  4. Train and evaluate the models
  5. Deploy the Web service
  6. Access the Web service

To use Machine Learning Studio, you need to have a Microsoft Azure Machine Learning workspace. This workspace contains the tools you need to create, manage, and publish experiments.

The administrator for your Azure subscription needs to create the workspace and then add you as an owner or contributor. For details, see Create and share an Azure Machine Learning workspace.

After your workspace is created, open Machine Learning Studio (https://studio.azureml.net/Home). If you have more than one workspace, you can select the workspace in the toolbar in the upper-right corner of the window.

Select workspace in Studio


If you were made an owner of the workspace, you can share the experiments you're working on by inviting others to the workspace. You can do this in Machine Learning Studio on the SETTINGS page. You just need the Microsoft account or organizational account for each user.

On the SETTINGS page, click USERS, then click INVITE MORE USERS at the bottom of the window.

Next: Upload existing data