Using Azure ML Workspace

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Azure Machine Learning Workspace acts as a centralized hub for managing and tracking all of your machine learning activities, providing a unified location to manage the artifacts generated by Azure Machine Learning. It contains tools for experimenting with, training, and deploying machine learning models.

DeepSense Azure Machine Learning Workspace

DeepSense has acquired Azure Machine Learning Workspaces to provide users with seamless access to the various features for developing machine learning projects. Navigate to the Notebooks section of your workspace to access your notebooks. In the User files section of your workspace, you can edit existing notebooks or create new ones. When you want to run the cells in the notebook, choose a DeepSense Admin compute instance based on the project usecase. Azure Machine Learning has a repository of sample Jupyter notebooks that you can use to get started on your own machine learning projects. These samples are accessible via the Samples tab in your workspace's Notebooks section.

DeepSense Azure administrator will create DeepSense Microsoft user account. Admin will send you an email containing information about your account. and users will have access to the Azure ML Workspace for their project.

Accessing DeepSense Azure Portal

  • Open web browser and navigate to the Azure portal login page.
  • Enter the URL provided in correspondence email and continue.
  • Enter the user's temporary first password in the "Password" field provided by DeepSense Azure Admin.
  • You will be redirected to change the password on first login, create a new password.
  • Your new Microsoft account will be created which gives you access to Azure portal.
  • After signing in to the new Microsoft account, locate the security credentials in the right top corner, where the account number and user name is written.
  • Click on add MFA and follow the on-screen instructions to enable MFA.
  • Your account will be set after this, you can now proceed to Azure portal.

Accessing DeepSense Azure ML Workspace Notebook

  • Search for Azure ML and open your project workspace.
  • Navigate to the Notebooks section of your workspace in Azure Machine Learning studio.
  • Click on + Create file at the top right corner of the screen.
  • In the pop-up window, give your notebook a name and select Python as the file type.
  • Click on Create to create your new notebook.
  • From the top right corner of the notebook, attach the compute instance to use compute instance.
  • Stop the compute instance from the same menu where you started it.

It is necessary to stop the notebook instance in order to avoid being charged for not utilized hours. So, when you're finished, please stop the instance.