Configura Vertex AI Experiments

Vertex AI Experiments è supportato dall'SDK Agent Platform per Python e dalla consoleGoogle Cloud . Vertex AI Experiments richiede e dipende da Vertex ML Metadata.

Configura

Accedi al tuo account Google Cloud . Se non conosci Google Cloud, crea un account per valutare le prestazioni dei nostri prodotti in scenari reali. I nuovi clienti ricevono anche 300 $di crediti senza costi per l'esecuzione, il test e il deployment dei workload.

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

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

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

Verify that billing is enabled for your Google Cloud project.

Enable the required API.

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

Enable the API

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

Roles required to select or create a project

• Select a project: Selecting a project doesn't require a specific IAM role—you can select any project that you've been granted a role on.
• Create a project: To create a project, you need the Project Creator role (roles/resourcemanager.projectCreator), which contains the resourcemanager.projects.create permission. Learn how to grant roles.

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

Verify that billing is enabled for your Google Cloud project.

Enable the required API.

Roles required to enable APIs

To enable APIs, you need the serviceusage.services.enable permission. If you created the project, then you likely already have this permission through the Owner role (roles/owner). Otherwise, you can get this permission through the Service Usage Admin role (roles/serviceusage.serviceUsageAdmin). Learn how to grant roles.

Enable the API

1. Crea un service account. Consulta Creare un account di servizio con le autorizzazioni richieste.
2. Installa l'SDK Agent Platform per Python.
3. Verifica l'esistenza dell'archivio dei metadati default nel tuo progetto. (obbligatorio)
   • Per verificare se il tuo progetto dispone di default Metadata Store, vai alla pagina Metadata nella console Google Cloud .
   • Se l'archivio di metadati default non esiste, viene creato quando
     • esegui il primo PipelineJob,
     • oppure crea il tuo primo esperimento nell'SDK Agent Platform per Python.
       (Facoltativo) Per la configurazione con CMEK, consulta Configurazione dell'archivio dei metadati del progetto.

Località supportate

La tabella Disponibilità delle funzionalità elenca le località disponibili per Vertex AI Experiments. Quando utilizzi le pipeline di Agent Platform o Vertex AI TensorBoard, devono trovarsi nella stessa località dell'esperimento di Agent Platform.

Passaggi successivi

• Creare un esperimento

Tutorial sui notebook pertinenti

1. Confrontare i modelli addestrati e valutati
2. Addestramento del modello con codice di pretrattamento dei dati predefinito
3. Confrontare le esecuzioni della pipeline
4. Registrazione automatica