Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Resource TrainingPipeline AutoML mengorkestrasi tugas-tugas yang terkait
dengan pelatihan model AutoML. Resource ini selalu menjalankan
tugas pelatihan, dan secara opsional juga dapat mengekspor data dari Vertex AI
Dataset yang menjadi input pelatihan, mengupload Model ke
Vertex AI, dan mengevaluasi Model. Untuk mengetahui informasi tentang
pelatihan AutoML di Vertex AI, lihat
dokumentasi pelatihan AutoML. Untuk mengetahui informasi
tentang Google Cloud Komponen Pipeline yang terkait dengan set data, lihat
Komponen set data.
Google Cloud SDK mencakup operator berikut yang terkait dengan
model dan alur kerja AutoML:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-02 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)."]]
