Hello text data: Cleaning up your project

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:

  1. Setting up your project and environment.

  2. Creating a text classification dataset .

  3. Training an AutoML text classification model.

  4. Deploy model to an endpoint and send a prediction.

  5. Cleaning up your project.

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

Deleting AI Platform (Unified) resources

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

Deleting your endpoint

  1. In the Google Cloud Console, in the AI Platform (Unified) section, go to the Endpoints page.

    Go to the Endpoints page

  2. Find your endpoint, click View more . Then click Remove endpoint.

  3. In the Remove endpoint dialog, click Confirm.

Deleting your model

  1. In the Google Cloud Console, in the AI Platform (Unified) section, go to the Models page.

    Go to the Models page

  2. Find your model, click View more . Then click Delete model.

  3. In the Delete model dialog, click Delete.

Deleting your dataset

  1. In the Google Cloud Console, in the AI Platform (Unified) section, go to the Datasets page.

    Go to the Datasets page

  2. Find your dataset, 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 you setup your project.

What's next