Clean up the Google Cloud resources that you created during this tutorial. Follow these steps to avoid incurring unexpected charges.
This tutorial has several pages:
Cleaning up your project.
Each page assumes that you have already performed the instructions from the previous pages of the tutorial.
Delete Vertex AI resources
This section describes how to delete the following project resources: endpoint, model, dataset, and Cloud Storage bucket.
Delete your endpoint
In the Google Cloud console, go to the Endpoints page.
Click your endpoint.
On the endpoint details page, find the row for your model. Click > Undeploy model from endpoint.View more
In the Undeploy model from endpoint dialog, click Undeploy.
Go back to the Endpoints page.
Find your endpoint, click > Delete endpoint.View more
In the Delete endpoint dialog, click Confirm.
Delete your model
In the Google Cloud console, go to the Model Registry page.
Find your model, click > Delete model.View more
In the Delete model dialog, click Delete.
Delete your dataset
In the Google Cloud console, in the Vertex AI section, go to the Datasets page.
Find your dataset, click > Delete dataset.View more
Delete your Cloud Storage bucket
- In the Google Cloud console, go to the Cloud Storage Browser page.
- Click the checkbox for the bucket that you want to delete.
- To delete the bucket, click Delete, and then follow the instructions.
Cloud Shell session
No action is required. Cloud Shell incurs no charges, and it automatically deletes your home disk after a period of inactivity.
To learn about additional ways to train ML models on Vertex AI, try one of the other Vertex AI tutorials.
Read an overview of how Vertex AI works.