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Vertex AI Experiments wird vom Vertex AI SDK für Python und derGoogle Cloud -Konsole unterstützt. Vertex AI Experiments erfordert und hängt von Vertex ML Metadata ab.
Einrichten
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.
Prüfen Sie, ob der default-Metadatenspeicher in Ihrem Projekt vorhanden ist. (erforderlich)
Wenn Sie prüfen möchten, ob Ihr Projekt den default-Metadatenspeicher hat, rufen Sie in der Google Cloud Console die Seite Metadata auf.
Wenn der default-Metadatenspeicher nicht vorhanden ist, wird er erstellt, wenn
Sie den ersten PipelineJob ausführen,
Alternativ können Sie Ihren ersten Test im Vertex AI SDK für Python erstellen.
Optional: Informationen zur Konfiguration mit CMEK finden Sie unter Metadatenspeicher Ihres Projekts konfigurieren.
Unterstützte Standorte
In der Tabelle Featureverfügbarkeit werden die verfügbaren Standorte für Vertex AI Experiments aufgeführt. Wenn Sie Vertex AI-Pipelines oder Vertex AI TensorBoard verwenden, müssen diese sich am selben Standort wie Ihr Vertex AI-Test befinden.
[[["Leicht verständlich","easyToUnderstand","thumb-up"],["Mein Problem wurde gelöst","solvedMyProblem","thumb-up"],["Sonstiges","otherUp","thumb-up"]],[["Schwer verständlich","hardToUnderstand","thumb-down"],["Informationen oder Beispielcode falsch","incorrectInformationOrSampleCode","thumb-down"],["Benötigte Informationen/Beispiele nicht gefunden","missingTheInformationSamplesINeed","thumb-down"],["Problem mit der Übersetzung","translationIssue","thumb-down"],["Sonstiges","otherDown","thumb-down"]],["Zuletzt aktualisiert: 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)"]]
