您可以通过 Vertex AI SDK for Python 和Google Cloud 控制台使用 Vertex AI Experiments。Vertex AI Experiments 需要并依赖于 Vertex ML Metadata。
设置
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.
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-09-04。"],[],[],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)"]]
