Creating a workbench

Launch a Workbench

  • Once the Data Connection and Pipeline Server are fully created

  • Create a workbench 02-03-create-wb.png

  • Make sure it has the following characteristics:

    • Choose a name for it, like: My Workbench
    • Image Selection: CUSTOM Crazy train lab
    • Container Size: Small
    • Keep the default cluster storage settings
    • On the bottom, tick “Use a data connection”
    • Scroll down to “Use existing data connection”
    • Select from the list the “pipelines” data connection you previously created.
    • That should look like: 02-02-launch-workbench-01.png 02-02-launch-workbench-02.png

  • Create the workbench and wait for your workbench status to be “Running”

  • Once it is, click the Open Link to connect to it. 02-03-open-link.png

  • Authenticate with the same credentials as earlier

  • You will be asked to accept the following settings: 02-02-accept.png

  • Do so

  • You should now see this: 02-02-jupyter.png

Git-Clone the lab repo

We will clone the content of our Git repo so that you can access all the materials that were created as part of our prototyping exercise.

  • Using the Git UI:
    • Open the Git UI in Jupyter: git-clone-1.png
  • Enter the URL of the Git repo: https://github.com/Demo-AI-Edge-Crazy-Train/workshop-model-training. Select also “Download the repository”. git-clone-2.png

At this point, your project is ready for the work we want to do in it.