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Lab 0: Setting up your environment

If a lab environmnet has not be provided for you, this lab provides the instructions to get started in your own Azure Subscription.

The following summarizes the lab requirements if you want to setup your own environment (for example, on your local machine). If this is your first time peforming these labs, it is highly recommended you follow the Quick Start instructions below rather that setup your own environment from scratch.

The labs have the following requirements:

  • Azure subscription. You will need a valid and active Azure account to complete this Azure lab. If you do not have one, you can sign up for a free trial.
  • One of the following environments:
    • Visual Studio 2017 and the Visual Studio Tools for AI
    • PyCharm
    • Azure Databricks Workspace
  • For the deep learning lab, you will need a VM or cluster with CPU capabilities.

Depending on which environment you use, there are different requirements. These are summarized as follows:

  • Visual Studio 2017 and PyCharm
    • A Python 3.x Anaconda environment named azureml with:
      • The latest version of the Azure Machine Learning Python SDK installed. Use pip install --upgrade azureml-sdk[notebooks,automl] azureml-dataprep to install the latest version.
      • The following pip installable packages:
        • numpy, pandas, scikitlearn, keras and tensorflow-gpu
    • For the deep learning lab, make sure you have your GPU drivers properly installed.
  • Azure Databricks
    • An Azure Databricks Workspace
    • A two-node Azure Databricks cluster with the following Python libraries attached: - numpy, pandas, scikitlearn, keras and tensorflow-gpu

The following sections describe the setup process for each environment.

Quickstart: Visual Studio 2017 and PyCharm

The quickest way to get going with the labs is to deploy the Deep Learning Virtual Machine (DLVM).

  1. Follow these instructions for creating an Deep Learning Virtual Machine. Be sure you do the following:
    • OS Type: Select Windows 2016
    • Location: Choose a region that provides NC series VM's, such as East US, East US 2, North Central US, South Central US and West US 2. Be sure to visit the Azure Products by Region website for the latest.
    • Virtual Machine size: NC6
  2. Once the VM is ready, download the remote desktop (RDP) file from the Overview blade of your VM in the Azure Portal and login. If you are unfamiliar with this process, see Connect to a VM.
  3. Once you are connected to your DLVM, open the Start Menu and run Anaconda Prompt.
  4. Activate the azureml conda environment by running activate azureml.
  5. To ensure tensorflow uses a GPU, you will need to uninstall and reinstall Keras and Tensorflow in a specific order. Run these commands in sequence:
    • pip uninstall keras
    • pip uninstall tensorflow-gpu
    • pip uninstall tensorflow
    • pip install keras
    • pip install tensorflow-gpu==1.10.0
  6. Upgrade the installed version of the Azure Machine Learning SDK by running the following command:
    • pip install --upgrade azureml-sdk[notebooks,automl] azureml-dataprep
  7. If you will be using Visual Studio for the labs, launch Visual Studio 2017 from the Start menu and login with your Microsoft Account. Allow Visual Studio a few moments to get ready. Once you see the Tools for AI Start Page displayed in Visual Studio, the setup is complete.
  8. If you will be using PyCharm for the labs, launch JetBrains PyCharm Community Edition from the Start menu. On the Complete Installation dialog, leave Do not import settings selected, accept the license agreement and choose an option for Data Sharing. On the Customize PyCharm screen, select Skip Remaining and Set Defaults. Once you are at the Welcome to PyCharm new project dialog the setup is complete.
  9. Your Virtual Machine is now ready to support any of the labs using either the Visual Studio or PyCharm environments.

Quickstart: Azure Databricks

  1. Click the following button to open the ARM template in the Azure Portal. Deploy Databricks from the ARM Template

  2. Provide the required values to create your Azure Databricks workspace:

    • Subscription: Choose the Azure Subscription in which to deploy the workspace.
    • Resource Group: Leave at Create new and provide a name for the new resource group.
    • Location: Select a location near you for deployment that supports both Azure Databricks AND provides NC series GPU enabled Virtual Machines. This currently includes East US, East US 2, North Central US, South Central US and West US 2. For the latest list, see Azure services available by region.
    • Workspace Name: Provide a name for your workspace.
    • Pricing Tier: Ensure premium is selected.

  3. Accept the terms and conditions.

  4. Select Purchase.

  5. The workspace creation takes a few minutes. During workspace creation, the portal displays the Submitting deployment for Azure Databricks tile on the right side. You may need to scroll right on your dashboard to see the tile. There is also a progress bar displayed near the top of the screen. You can watch either area for progress.