Hello video data: Clean up your project

Clean up the Google Cloud resources that you created to train and get predictions from your AutoML video classification model. Follow these steps to avoid incurring unexpected charges from some of the resources.

This tutorial has several pages:

1. Setting up your project.

2. Creating a video classification dataset.

3. Training an AutoML video classification model.

4. Deploying the model for batch predictions.

5. Cleaning up your project.

Each page assumes that you've 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: model, dataset, and Cloud Storage bucket.

Delete your model

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 View more . Then click Delete model.

3. In the Delete model dialog, click Delete.

Delete your dataset

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 View more . Then click Delete dataset.

Clean up your Cloud Shell session

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

Delete your Cloud Storage bucket

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, and then follow the instructions.

What's next

• 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.