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Showing content from https://cloud.google.com/vertex-ai/docs/tutorials/image-classification-automl/cleanup below:

Hello image data: Clean up your project | Vertex AI

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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:

1. Set up your project and environment.

2. Create an image classification dataset, and import images.

3. Train an AutoML image classification model.

4. Evaluate and analyze model performance.

5. Deploy a model to an endpoint, and send a prediction.

6. Clean up your project.

Each page assumes that you have already performed the instructions from the previous pages of the tutorial.

This section describes how to undeploy your model, and then delete the following project resources: endpoint, model, dataset, and Cloud Storage bucket.

Before you can delete your model and endpoint, you must undeploy the model.

1. In the Google Cloud console, in the Vertex AI section, go to the Training page.

   Go to the Training page

2. Select your trained AutoML model. This takes you to the Evaluate tab.

3. Click the Deploy & test tab.

4. Find your model. On your model's row, click the three vertical dots more_vert, then click Undeploy model.

5. In Undeploy model, click Confirm.

1. In the Google Cloud console, in the Vertex AI section, go to the Endpoints page.

   Go to the Endpoints page

2. Find your endpoint, hello_automl_image. On that row, click the three vertical dots more_vert, then click Remove endpoint.

3. In Remove endpoint, click Confirm.

1. In the Google Cloud console, in the Vertex AI section, go to the Models page.

   Go to the Models page

2. Find your model. On that row, click the three vertical dots more_vert, then click Delete model.

3. In Delete model and all of its associated versions, click Delete.

1. In the Google Cloud console, in the Vertex AI section, go to the Datasets page.

   Go to the Datasets page

2. Find your dataset. On that row, click the three vertical dots more_vert, then click Delete dataset.

3. In Delete dataset, click Delete.

Cloud Shell incurs no charges, and it automatically deletes your home disk after a period of inactivity.

1. In the Google Cloud console, go to the Cloud Storage Buckets page.

   Go to Buckets

2. Click the checkbox for the bucket that you want to delete.
3. To delete the bucket, click delete Delete, and then follow the instructions.

• 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.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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