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Simpan dan kategorikan konten berdasarkan preferensi Anda.
Anda dapat menggunakan set data terkelola untuk menyediakan data sumber yang digunakan untuk melatih AutoML dan model kustom di Vertex AI. Set data terkelola diperlukan untuk AutoML dan bersifat opsional untuk pelatihan kustom.
Membuat set data terkelola untuk model AutoML
Anda dapat membuat set data terkelola untuk melatih model AutoML menggunakanGoogle Cloud konsol atau Vertex AI API. Petunjuk cara melakukannya sedikit bervariasi berdasarkan jenis data dan objektif model Anda. Mulailah dengan menyiapkan data pelatihan Anda.
Gambar
Pelajari cara membuat set data terkelola untuk jenis model AutoML gambar berikut:
Melihat set data terkelola menggunakan Data Catalog
Data Catalog adalah layanan pengelolaan metadata yang skalabel dan terkelola sepenuhnya yang menyediakan lokasi terpusat untuk menelusuri set data di berbagai project dan region.
[[["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 2025-08-18 UTC."],[],[],null,["# Overview of creating managed datasets on Vertex AI\n\nYou can use a managed dataset to provide the source data used\nto train AutoML and custom models on Vertex AI. A managed\ndataset is required for AutoML and is optional for\ncustom training.\n\nCreate a managed dataset for AutoML models\n------------------------------------------\n\nYou can create managed datasets for training AutoML models by using the\nGoogle Cloud console or the Vertex AI API. The instructions for how to do this\nslightly vary based on your data type and model objective. Start by preparing\nyour training data.\n\n### Image\n\nLearn how to create a managed dataset for the following types of image\nAutoML models:\n\n- [Image classification models](/vertex-ai/docs/image-data/classification/prepare-data)\n- [Image object detection models](/vertex-ai/docs/image-data/object-detection/prepare-data)\n\n### Tabular\n\nLearn how to create a managed dataset for the following types of tabular\nAutoML models:\n\n- [Tabular classification and regression models](/vertex-ai/docs/tabular-data/classification-regression/prepare-data)\n- [Tabular forecasting models](/vertex-ai/docs/tabular-data/forecasting/prepare-data)\n\n### Video\n\nLearn how to create a managed dataset for the following types of video\nAutoML models:\n\n- [Video action recognition models](/vertex-ai/docs/video-data/action-recognition/prepare-data)\n- [Video classification models](/vertex-ai/docs/video-data/classification/prepare-data)\n- [Video object tracking models](/vertex-ai/docs/video-data/object-tracking/prepare-data)\n\nCreate a managed dataset for custom trained models\n--------------------------------------------------\n\nThe instructions on how to create a managed dataset for training custom models\nare the same, regardless of your data type or model objective.\n\nFor details, see\n[Use managed datasets](/vertex-ai/docs/training/using-managed-datasets).\n\nView managed datasets using Data Catalog\n----------------------------------------\n\nData Catalog is a fully managed, scalable metadata management service\nthat provides a centralized location to search for datasets\nacross projects and regions.\n\nFor details, see\n[Use Data Catalog to search for model and dataset resources](/vertex-ai/docs/model-registry/model-data-catalog)\noverview."]]
