Workbench Creation

Launch a Workbench

Once the Data Connection and the Pipeline Server have been fully created, you can proceed to create the Workbench, which will serve as the main environment for AI development.

  1. Click on the Workbenches tab, then click the Create workbench button.
    02-03-create-wb.png

  2. Fill in the following settings in the form:

  • Name: choose a name, for example My Workbench
  • Image selection: select CUSTOM Crazy train lab
  • Container size: select Small
  • Use a data connection: check this option, then select Use existing data connection. From the dropdown, choose the pipelines Data Connection you created earlier.

The result should look like this:
02-02-launch-workbench-01.png
02-02-launch-workbench-02.png

  1. Click Create workbench to confirm, and wait for the blue Starting status to turn green Running.

  2. Once the Workbench is created, click the Open link to access it.
    02-03-open-link.png

  3. Log in using the same credentials as before.

  4. You will be prompted to accept some settings. Click Allow selected permissions.
    02-02-accept.png

You should now see the following interface:
02-02-jupyter.png

Clone the Git Repository

We will clone the content of our Git repository so that you can access all the materials needed for AI model training.

  1. Open the tab with the Git icon in the left menu and click Clone a Repository:
    git-clone-1.png

  2. Enter the Git repository URL: https://github.com/Demo-AI-Edge-Crazy-Train/workshop-model-training. Also check Download the repository, then click Clone:
    git-clone-2.png

At this stage, your Jupyter environment is ready to start working.