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Vertex AI Experiments è supportato dall'SDK Vertex AI per Python e dalla
consoleGoogle Cloud . Vertex AI Experiments richiede e dipende da
Vertex ML Metadata.
Configura
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.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
La tabella Disponibilità delle funzionalità elenca le località disponibili per Vertex AI Experiments. Quando utilizzi
Vertex AI Pipelines o Vertex AI TensorBoard,
devono trovarsi nella stessa località dell'esperimento Vertex AI.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-04 UTC."],[],[],null,["# Set up for Vertex AI Experiments\n\nVertex AI Experiments is supported by the Vertex AI SDK for Python and\nGoogle Cloud console. Vertex AI Experiments requires and depends on\n[Vertex ML Metadata](/vertex-ai/docs/ml-metadata/introduction).\n\nSet up\n------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **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.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the required API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **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.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the required API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=aiplatform.googleapis.com)\n\n1. Create a Service account. See [Create a service account with required permissions](/vertex-ai/docs/experiments/tensorboard-training#create_a_service_account_with_required_permissions).\n2. Install the [Vertex AI SDK for Python.](/vertex-ai/docs/start/install-sdk)\n3. Check for existence of the `default` Metadata Store in your project. (required)\n - To see if your project has the `default` Metadata Store, go to the `Metadata` page in the Google Cloud console.\n - If the `default` Metadata Store doesn't exist, it's created when\n - you run the first ,\n - or, create your first experiment in the Vertex AI SDK for Python. \n Optional: To configure with CMEK, see [Configure your project's metadata store.](/vertex-ai/docs/ml-metadata/configure)\n\nSupported Locations\n-------------------\n\nThe [Feature availability](/vertex-ai/docs/general/locations#americas_1) table lists the available locations for Vertex AI Experiments. When using\nVertex AI Pipelines or Vertex AI TensorBoard,\nthey must be in the same location as your Vertex AI experiment.\n\nWhat's next\n-----------\n\n- [Create an experiment](/vertex-ai/docs/experiments/create-experiment)\n\nRelevant notebook tutorials\n---------------------------\n\n1. [Compare trained and evaluated models](/vertex-ai/docs/experiments/user-journey/uj-compare-models)\n2. [Model training with prebuilt data pre-processing code](/vertex-ai/docs/experiments/user-journey/uj-model-training)\n3. [Compare pipeline runs](/vertex-ai/docs/experiments/user-journey/uj-compare-pipeline-runs)\n4. [Autologging](/vertex-ai/docs/experiments/user-journey/uj-autologging)"]]
