Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Vertex AI Model Registry adalah repositori pusat tempat Anda dapat mengelola
siklus proses model ML. Dari Model Registry,
Anda memiliki ringkasan model sehingga dapat mengatur, melacak,
dan melatih versi baru dengan lebih baik. Jika memiliki versi model yang ingin di-deploy,
Anda dapat menetapkannya ke endpoint langsung dari registry, atau dengan menggunakan alias, Anda dapat men-deploy model ke endpoint.
Vertex AI Model Registry mendukung model kustom dan semua jenis data AutoML, yaitu tabulasi, gambar, dan video. Model Registry
juga dapat mendukung model BigQuery ML. Jika memiliki model yang dilatih di
BigQuery ML, Anda dapat mendaftarkannya dengan
Model Registry tanpa perlu mengekspornya dari
BigQuery ML atau mengimpornya ke Model Registry.
Dari halaman detail versi model, Anda dapat mengevaluasi, men-deploy ke endpoint,
menyiapkan inferensi batch, dan melihat detail model tertentu. Vertex AI Model Registry
menyediakan antarmuka yang mudah dan disederhanakan untuk mengelola dan men-deploy
model terbaik ke produksi.
Alur kerja umum
Ada banyak alur kerja yang valid untuk bekerja di Model Registry.
Untuk memulai, sebaiknya ikuti panduan ini guna memahami hal yang dapat
dilakukan di Model Registry dan pada tahap mana dalam perjalanan pelatihan model Anda.
Impor model ke Model Registry.
Buat model baru, tetapkan versi model sebagai alias default, yang siap untuk produksi.
Tambahkan alias atau label lain untuk membantu Anda mengelola dan mengatur model serta versi model.
Deploy model Anda ke endpoint untuk inferensi online.
Jalankan inferensi batch, lalu mulai pipeline evaluasi model Anda.
Lihat detail model Anda dan lihat metrik performa dari halaman detail model.
Untuk mempelajari lebih lanjut cara mengintegrasikan model BigQuery ML Anda dengan Vertex AI, lihat dokumentasi BigQuery ML.
Menelusuri dan menemukan model menggunakan Katalog Universal Dataplex
Dataplex Universal Catalog adalah platform untuk menyimpan, mengelola, dan mengakses metadata Anda. Dataplex Universal Catalog menyediakan cara untuk menelusuri model Vertex AI Anda 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 2025-08-19 UTC."],[],[],null,["# Introduction to Vertex AI Model Registry\n\n| To see an example of getting started with Vertex AI Model Registry,\n| run the \"Get started with Vertex AI Model Registry\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_registry/get_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fmodel_registry%2Fget_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fmodel_registry%2Fget_started_with_model_registry.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/model_registry/get_started_with_model_registry.ipynb)\n\nThe Vertex AI Model Registry is a central repository where you can manage\nthe lifecycle of your ML models. From the Model Registry,\nyou have an overview of your models so you can better organize, track,\nand train new versions. When you have a model version you would like to deploy,\nyou can assign it to an endpoint directly from the registry,\nor using aliases, deploy models to an endpoint.\n\nThe Vertex AI Model Registry supports custom models and all\nAutoML data types - tabular, image, and video. The\nModel Registry\ncan also support BigQuery ML models. If you have models trained in\nBigQuery ML, you can register them with the\nModel Registry without needing to export them from\nBigQuery ML or import them into the Model Registry.\n\nFrom the model version details page you can evaluate, deploy to an endpoint,\nset up batch inference, and view specific model details. The Vertex AI Model Registry\nprovides a straightforward and streamlined interface to manage and deploy your\nbest models to production.\n\nCommon workflow\n---------------\n\nThere are many valid workflows for working in the Model Registry.\nTo get started, you might want to follow these guidelines to understand what you can\ndo in the Model Registry and at what stage in your model-training journey.\n\n- Import models to the Model Registry.\n- Create new models, assign a model version the default alias, ready for production.\n- Add other aliases, or labels to help you manage and organize your models and model versions.\n- Deploy your models to an endpoint for online inference.\n- Run batch inference, and start your model evaluation pipeline.\n- View your model details and view performance metrics from the model details page.\n\nTo learn more about how to integrate your BigQuery ML models with\nVertex AI, see the\n[BigQuery ML documentation.](/bigquery-ml/docs/managing-models-vertex)\n\nSearch and discover models using Dataplex Universal Catalog\n-----------------------------------------------------------\n\nDataplex Universal Catalog is a platform for storing, managing, and accessing your\nmetadata. Dataplex Universal Catalog provides a way to search\nfor your Vertex AI models across projects and regions.\n\nFor more information, see [About data catalog management in\nDataplex Universal Catalog](/dataplex/docs/catalog-overview).\n\nWhat's next\n-----------\n\nTo get started using Vertex AI Model Registry, see:\n\n- [Import models to Vertex AI](/vertex-ai/docs/model-registry/import-model)\n- [Model versioning with Model Registry](/vertex-ai/docs/model-registry/versioning)\n- [How to use model version aliases](/vertex-ai/docs/model-registry/model-alias)\n- [BigQuery ML and Model Registry](/vertex-ai/docs/model-registry/model-registry-bqml)\n- [Copy a model in Vertex AI Model Registry](/vertex-ai/docs/model-registry/copy-model)"]]
