Clean up the Google Cloud resources that you created to train your image classification model and get predictions from it. Follow these steps to avoid incurring unexpected charges from some of the resources.
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.
Deleting Vertex AI resources
This section describes how to delete the following project resources: endpoint, model, dataset, and Cloud Storage bucket.
Deleting your endpoint
In the Google Cloud Console, in the Vertex AI section, go to the Endpoints page.
Find your endpoint,
hello_automl_image. On that row, click View more . Then click Remove endpoint.
In the Remove endpoint dialog, click Confirm.
Deleting your model
In the Google Cloud Console, in the Vertex AI section, go to the Models page.
Find your model. On that row, click View more. Then click Delete model.
In the Delete model dialog, click Delete.
Deleting your dataset
In the Google Cloud Console, in the Vertex AI section, go to the Datasets page.
Find your dataset. On that row, click View more. Then click Delete dataset.
Cleaning up your Cloud Shell session
Cloud Shell incurs no charges, and it automatically deletes your home disk after a period of inactivity.
Deleting your Cloud Storage bucket
In your Cloud Shell session, run the following command:
gsutil -m rm -rf gs://BUCKET_NAME
Replace BUCKET_NAME with the name of the Cloud Storage bucket that you created when reading the first page of this tutorial.
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.