Set up for Vertex AI Experiments

Vertex AI Experiments is supported by the Vertex AI SDK for Python and Google Cloud console. Vertex AI Experiments requires and depends on Vertex ML Metadata.

Set up

• Follow steps 1-3 in Set up a project and a development environment.
• Create a Service account. See Create a service account with required permissions.
• Install the Vertex AI SDK for Python.
• Check for existence of the default Metadata Store in your project. (required)
  • To see if your project has the default Metadata Store, go to the Metadata page in the Google Cloud console.
  • If the default Metadata Store doesn't exist, it's created when
    • you run the first PipelineJob,
    • or, create your first experiment in the Vertex AI SDK for Python.
      Optional: To configure with CMEK, see Configure your project's metadata store.

Supported Locations

The Feature availability table lists the available locations for Vertex AI Experiments. When using Vertex AI Pipelines or Vertex AI TensorBoard, they must be in the same location as your Vertex AI experiment.

What's next

• Create an experiment

Relevant notebook tutorials

1. Compare trained and evaluated models
2. Model training with prebuilt data pre-processing code
3. Compare pipeline runs
4. Autologging