Manage BigQuery ML models in Vertex AI

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You can register BigQuery ML models with the Vertex AI Model Registry, in order to manage them alongside your other ML models without needing to export them. When you integrate your models with Vertex AI Model Registry, you can version, evaluate, and deploy your models for online prediction using a single interface and without needing a serving container. If you aren't familiar with Vertex AI and want to learn more about how it integrates with BigQuery ML, see Vertex AI for BigQuery users.

To learn more about Vertex AI prediction, see Overview of getting predictions on Vertex AI.

To learn how to manage your BigQuery ML models from Vertex AI Model Registry, see Introduction to Vertex AI Model Registry.

Prerequisites

To add BigQuery ML models to the Vertex AI Model Registry, you'll need to enable Vertex AI API in your project. Use this gCloud command:

gcloud --project PROJECT_ID services enable  aiplatform.googleapis.com

The credentials required for running this job need to have Vertex AI permissions. For more details, see Access control with IAM.

Use this command to grant Vertex AI Model Registry permission to your service account:

gcloud projects add-iam-policy-binding PROJECT_ID --member=serviceAccount:YOUR_SERVICE_ACCOUNT --role=roles/aiplatform.admin --condition=None

If you are not owner of your project, use this command to grant Vertex AI Model Registry permission to your account:

gcloud projects add-iam-policy-binding PROJECT_ID --member=user:YOUR_GCLOUD_ACCOUNT --role=roles/aiplatform.admin --condition=None

Considerations

What happens when I register a multi-region BigQuery ML model to Vertex AI Model Registry?

At this time, if you decide to add a multi-region BigQuery ML model to Vertex AI Model Registry it turns the model into a regional model in Vertex AI. A BigQuery ML US multi-region model is synced to Vertex AI (us-central1) and a BigQuery ML multi-region EU model is synced to Vertex AI (europe-west4). For single region models, there are no changes.

For information about how to update model locations, see Locations in the Vertex AI Resources documentation.

Can I use XAI capabilities in Vertex AI Model Registry with BigQuery ML models?

At this time you can use BigQuery ML Explainable AI only, XAI capabilities are not supported for Vertex AI Model Registry. To learn more, see BigQuery Explainable AI Overview.

Notebook

To get started using Vertex AI Model Registry and BigQuery ML, use one of the available notebooks:

What do you want to do? Resource
Train a model using BigQuery ML, register the model to Vertex AI Model Registry, and deploy it to an endpoint for real-time prediction. Online prediction with BigQuery ML BigQuery ML
Train a model with BigQuery ML and upload it on Vertex AI Model Registry, then make batch predictions. Deploy BigQuery ML model on Vertex AI Model Registry and make predictions.

To learn more about Vertex AI Model Registry, see Introduction to Vertex AI Model Registry.