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La risorsa AutoML TrainingPipeline coordina le attività associate
all'addestramento di un modello AutoML. Questa risorsa esegue sempre l'attività di addestramento e, facoltativamente, può anche esportare dati da un Dataset Vertex AI che diventa l'input di addestramento, caricare il modello su Vertex AI e valutarlo. Per informazioni sull'addestramento AutoML in Vertex AI, consulta la documentazione sull'addestramento AutoML. Per informazioni
sui Google Cloud componenti della pipeline correlati ai set di dati, consulta
Componenti del set di dati.
L'SDK Google Cloud include i seguenti operatori correlati a
modelli e flussi di lavoro AutoML:
[[["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,["# Vertex AI AutoML components\n\nThe AutoML `TrainingPipeline` resource orchestrates tasks associated\nwith training an AutoML model. This resource always executes the\ntraining task, and optionally may also export data from a Vertex AI\n`Dataset` which becomes the training input, upload the Model to\nVertex AI, and evaluate the Model. For information about\nAutoML training in Vertex AI, see the\n[AutoML training documentation](/vertex-ai/docs/training-overview#automl). For information\nabout Google Cloud Pipeline Components related to datasets, see\n[Dataset components](/vertex-ai/docs/pipelines/dataset-component).\n\nThe Google Cloud SDK includes the following operators related to\nAutoML models and workflows:\n\n**Operators related to AutoML forecasting**\n\n\n- [`ProphetTrainerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/forecasting.html#v1.automl.forecasting.ProphetTrainerOp)\n\n\u003cbr /\u003e\n\n**Operators related to AutoML Tabular models**\n\n\n- [`CvTrainerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.CvTrainerOp)\n- [`EnsembleOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.EnsembleOp)\n- [`FinalizerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.FinalizerOp)\n- [`InfraValidatorOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.InfraValidatorOp)\n- [`SplitMaterializedDataOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.SplitMaterializedDataOp)\n- [`Stage1TunerOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.Stage1TunerOp)\n- [`StatsAndExampleGenOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.StatsAndExampleGenOp)\n- [`TrainingConfiguratorAndValidatorOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.TrainingConfiguratorAndValidatorOp)\n- [`TransformOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/tabular.html#v1.automl.tabular.TransformOp)\n\n\u003cbr /\u003e\n\n**Operators related to AutoML `model` resource creation**\n\n\n- [`AutoMLForecastingTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLForecastingTrainingJobRunOp)\n- [`AutoMLImageTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLImageTrainingJobRunOp)\n- [`AutoMLTabularTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLTabularTrainingJobRunOp)\n- [`AutoMLTextTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_job.AutoMLTextTrainingJobRunOp)\n- [`AutoMLVideoTrainingJobRunOp`](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html#v1.automl.training_jobAutoMLVideoTrainingJobRunOp)\n\n\u003cbr /\u003e\n\n[Learn more about training and using your own AutoML models](/vertex-ai/docs/training-overview#automl).\n\nAPI reference\n-------------\n\n- For AutoML component reference, see the\n [Google Cloud SDK reference for AutoML components](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/api/v1/automl/training_job.html).\n\n- For Vertex AI API reference, see the following API reference pages:\n\n - [`Dataset` resource](/vertex-ai/docs/reference/rest/v1/projects.locations.datasets)\n\n - [`TrainingPipeline` resource](/vertex-ai/docs/reference/rest/v1/projects.locations.trainingPipelines)\n\nTutorials\n---------\n\n- [Learn how to use the Google Cloud pipeline components to train an image classification model using Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_images.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a classification model using tabular data and Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/automl_tabular_classification_beans.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a linear regression model using tabular data and Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_tabular.ipynb)\n- [Learn how to use the Google Cloud pipeline components to train a text classification model using Vertex AI AutoML.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_automl_text.ipynb)\n- [Learn how to use the Google Cloud pipeline components to upload and deploy a model.](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/pipelines/google_cloud_pipeline_components_model_train_upload_deploy.ipynb)\n\nVersion history and release notes\n---------------------------------\n\nTo learn more about the version history and changes to the Google Cloud Pipeline Components SDK, see the [Google Cloud Pipeline Components SDK Release Notes](https://google-cloud-pipeline-components.readthedocs.io/en/google-cloud-pipeline-components-2.19.0/release.html).\n\n### Technical support contacts\n\nIf you have any questions, reach out to\n[kubeflow-pipelines-components@google.com](mailto: kubeflow-pipelines-components@google.com)."]]