Manage BigQuery ML models in Vertex AI
You can register BigQuery ML models with the Model Registry, in order to manage them alongside your other ML models without needing to export them. When you integrate your models with 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.
- Add BigQuery ML model to the Model Registry
- Update a BigQuery ML model in the Model Registry
- View BigQuery ML evaluations from Model Registry
- Remove a BigQuery ML model from Model Registry
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 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 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 Model Registry?
At this time, if you decide to add a multi-region BigQuery ML model to 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 Model Registry with BigQuery ML models?
At this time you can use BigQuery ML Explainable AI only, XAI capabilities are not supported for Model Registry. To learn more, see BigQuery ML explainable AI overview.
Notebook
To get started using 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 Model Registry, and deploy it to an endpoint for real-time prediction. | Online prediction with BigQuery ML |
| Train a model with BigQuery ML and upload it on Model Registry, then make batch predictions. | Deploy BigQuery ML model on Model Registry and make predictions. |
To learn more about Model Registry, see Introduction to Model Registry.