Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Dapatkan paket dukungan Google
Google Cloud menawarkan paket dukungan yang berbeda untuk memenuhi berbagai kebutuhan, seperti
cakupan 24/7, dukungan telepon, dan akses ke pengelola dukungan teknis. Untuk
mengetahui informasi selengkapnya, lihat Cloud Customer Care.
Mendapatkan dukungan dari komunitas
Mengajukan pertanyaan di Google Cloud Komunitas
Ajukan pertanyaan tentang Vertex AI di Google Cloud
Komunitas.
Gunakan tag Vertex AI Platform untuk pertanyaan tentang
Vertex AI. Tag ini tidak hanya menerima respons dari komunitas, tetapi juga dari engineer Google, yang memantau tag dan menawarkan dukungan tidak resmi.
Mendapatkan dukungan untuk framework machine learning
Vertex AI menyediakan container bawaan dengan framework
machine learning (ML) berikut: PyTorch, scikit-learn, TensorFlow, dan
XGBoost. Penggunaan container bawaan ini di Vertex AI sepenuhnya
didukung oleh SLA dan tercakup dalam opsi dukungan standar.
Vertex AI menyediakan layanan terkelola yang mengimplementasikan Kubeflow SDK:
Vertex AI Pipelines. Penggunaan Vertex AI Pipelines didukung sepenuhnya oleh SLA dan dicakup
oleh opsi dukungan standar.
Kubeflow open source yang berjalan di cluster GKE tidak tercakup dalam opsi dukungan standar.
Untuk mendapatkan dukungan framework ML, termasuk masalah dokumentasi dan bug yang tidak terkait dengan Vertex AI, gunakan opsi dukungan framework ML tersebut:
Anda juga dapat mengirimkan masalah produk atau dokumentasi dengan mengklik tombol
Kirim masukan di halaman dokumentasi yang relevan.
Tindakan ini akan membuka formulir masukan. Masukan produk Anda akan ditinjau oleh tim Vertex AI. Masukan dokumentasi akan
ditinjau oleh tim dokumentasi Vertex AI.
[[["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 2025-09-04 UTC."],[],[],null,["# Get support\n\nGet a Google support package\n----------------------------\n\nGoogle Cloud offers different support packages to meet different needs, such as\n24/7 coverage, phone support, and access to a technical support manager. For\nmore information, see [Cloud Customer Care](/support).\n\nGet support from the community\n------------------------------\n\n### Ask a question on Google Cloud Community\n\nAsk a question about Vertex AI on [Google Cloud\nCommunity](https://www.googlecloudcommunity.com/gc/forums/filteredbylabelpage/board-id/cloud-ai-ml/label-name/vertex%20ai%20platform/).\nUse the tag `Vertex AI Platform` for questions about\nVertex AI. This tag not only receives responses\nfrom the community but also from Google engineers, who monitor the tag and\noffer unofficial support.\n\nGet support for machine learning frameworks\n-------------------------------------------\n\nVertex AI provides prebuilt containers with the following\nmachine learning (ML) frameworks: PyTorch, scikit-learn, TensorFlow, and\nXGBoost. Use of these prebuilt containers in Vertex AI is fully\nbacked by the SLA and covered by the standard support options.\n\nVertex AI provides a managed service which implements the Kubeflow SDK:\nVertex AI Pipelines. Using Vertex AI Pipelines is fully backed by the SLA and covered\nby the standard support options.\n\nOpen source Kubeflow running on a GKE cluster is **not** covered by the standard support options.\n\nTo get support for an ML framework, including for bugs and documentation issues\nunrelated to Vertex AI, use that ML framework's support options:\n\n- To get support for Pytorch, see the\n [PyTorch documentation](https://pytorch.org/docs/stable/index.html). To submit issues to PyTorch,\n see the [PyTorch issue tracker on GitHub](https://github.com/pytorch/pytorch/issues).\n\n- To get support for scikit-learn, see the\n [scikit-learn FAQ](https://scikit-learn.org/stable/faq.html). To submit issues to scikit-learn,\n see the [scikit-learn issue tracker on GitHub](https://github.com/scikit-learn/scikit-learn/issues).\n\n- To get support for TensorFlow, see the\n [TensorFlow documentation](https://www.tensorflow.org/). To submit issues to\n TensorFlow, see the\n [TensorFlow issue tracker on GitHub](https://github.com/tensorflow/tensorflow/issues).\n\n- To get support for XGBoost, see the [XGBoost FAQ](https://xgboost.readthedocs.io/en/latest/faq.html).\n To submit issues to XGBoost, see the\n [XGBoost issue tracker on GitHub](https://github.com/dmlc/xgboost/issues).\n\n- To get support for Kubeflow, see the [Kubeflow Docs](https://www.kubeflow.org/docs/).\n To submit issues to Kubeflow Pipelines, see the\n [Kubeflow issue tracker on GitHub](https://github.com/kubeflow/pipelines/issues).\n\nFile bugs or feature requests\n-----------------------------\n\nKeep track of Vertex AI issues on the\n[issue tracker](https://issuetracker.google.com/issues/new?component=1130925).\n\nYou can also submit product or documentation issues by clicking the\n**Send feedback** button on a relevant documentation page.\nThis opens a feedback form. Your product feedback will be\nreviewed by the Vertex AI team. Documentation feedback will be\nreviewed by the Vertex AI documentation team."]]
