Create a managed notebooks instance
Create a managed notebooks instance and specify the environment, hardware configuration, encryption type, network, security, and permissions.
Add a custom container to a managed notebooks instance
Add a custom container to a Vertex AI Workbench managed notebooks instance as a kernel to run your notebook files on.
Run a managed notebooks instance on a Dataproc cluster
Run a managed notebooks instance's notebook file on a Dataproc cluster.
Query data in BigQuery tables from within JupyterLab
Write BigQuery queries, get results, and load the results into a dataframe by using the JupyterLab interface.
Access Cloud Storage buckets and files from within JupyterLab
Browse Cloud Storage buckets and access compatible files from within JupyterLab.
Run notebook files with the executor
Use the executor in a Vertex AI Workbench managed notebooks instance to run notebook files as a one-time execution or on a schedule.
Run notebook executions with parameters
Use parameters in your execution to specify differences in each run. For example, you might specify a different dataset to use, change the learning rate on your model, or change the version of the model.