Creating a workbench and selecting a notebook image
A workbench is an instance of your development and experimentation environment. Within a workbench you can select a notebook image for your data science work.
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You created a
My Storagedata connection as described in Storing data with data connections. -
You configured a pipeline server as described in Enabling data science pipelines.
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Navigate to the project detail page for the data science project that you created in Setting up your data science project.
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Click the Workbenches tab, and then click the Create workbench button.
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Fill out the name and description.
Red Hat provides several supported notebook images. In the Notebook image section, you can choose one of these images or any custom images that an administrator has set up for you. The Tensorflow image has the libraries needed for this workshop.
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Select the latest Tensorflow image.
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Choose a small deployment.
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Leave the default environment variables and storage options.
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Under Data connections, select Use existing data connection and select
My Storage(the object storage that you configured previously) from the list.
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Click the Create workbench button.
In the Workbenches tab for the project, the status of the workbench changes from Starting to Running.
| If you made a mistake, you can edit the workbench to make changes. |
