Before you begin

The AutoML Natural Language product is available in the Vertex AI platform. Migrate your resources to Vertex AI AutoML text to get new machine learning features, simplify end-to-end journeys, and productionize models with MLOps.

Before you can use AutoML Natural Language, you must enable it for your project. Open the AutoML Natural Language UI and select the project. The application walks you through the necessary steps, which are also described below.

Set up your project

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

4. Enable the AutoML and Cloud Storage APIs.

   Enable the APIs

5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

6. Make sure that billing is enabled for your Cloud project. Learn how to check if billing is enabled on a project.

7. Enable the AutoML and Cloud Storage APIs.

   Enable the APIs

8. Install the gcloud command line tool.
9. Follow the instructions to create a service account and download a key file for that account.
   Service accounts are the only authentication option available with the AutoML API.
10. Set the GOOGLE_APPLICATION_CREDENTIALS environment variable to the path to the service account key file that you downloaded when you created the service account.

    export GOOGLE_APPLICATION_CREDENTIALS=KEY_FILE

11. Set the PROJECT_ID environment variable to your Project ID.

    export PROJECT_ID=PROJECT_ID

    The AutoML API calls and resource names include your Project ID in them. The PROJECT_ID environment variable provides a convenient way to specify the ID.
12. If you are an owner for your project, add your service account to the AutoML Editor IAM role, replacing SERVICE_ACCOUNT_NAME with the name of your new service account. For example, [e-mail].

    gcloud auth login
    gcloud projects add-iam-policy-binding $PROJECT_ID \
       --member="serviceAccount:SERVICE_ACCOUNT_NAME" \
       --role="roles/automl.editor"
    

13. Otherwise (if you are not a project owner), ask a project owner to add both your user ID and your service account to the AutoML Editor IAM role.

Create a Cloud Storage bucket

Create a Cloud Storage bucket for AutoML Natural Language tasks such as importing training data. The bucket must be in either the us-central1 region or eu multi-region location.

Bucket requirements for us-central1:

• Location type: Region
• Location: us-central1
• Storage class: Standard (sometimes displayed in the Cloud Storage browser as Regional)

Bucket requirements for eu:

• Location type: Multi-region
• Location: eu
• Storage class: Standard (sometimes displayed in the Cloud Storage browser as Multi-Regional)