ML expert Platform overview

Available in VPC

ML expert Platform provides efficient and reliable services across the entire AI/ML service workflow—from data management and processing to large-scale distributed training, as well as serving and deployment for models ranging from small to ultra-large AI models.

ML expert Platform user guide

Use this guide to get the most out of ML expert Platform.

• ML expert Platform overview: Learn about the service and find helpful resources.
• ML expert Platform prerequisites: View specifications and pricing information.
• ML expert Platform concepts: Explain key concepts to help you understand how to use ML expert Platform.
• ML expert Platform quickstart: Follow a step-by-step guide through the entire process.
• Getting started: Learn how to manage subscriptions and how to view usage.
• Using ML expert Platform
  • Workspace: Learn about the Workspace interface in ML expert Platform.
  • ML expert Platform Workspace
    • Workspace home screen: Learn about the Workspace home screen.
    • Dashboard: Describes Workspace member and project information, and how to manage API Keys.
    • Member settings: Describes how to add and delete Workspace members.
    • GPU resources: Describes how to view the GPU resources allocated to the Workspace and how to assign them to each project.
    • Data Manager: Describes view the list of datasets in the Workspace and check their details.
  • Project
    • Project home screen
      • Overview: Learn how to check a project's task history and how to download the kubeconfig file.
      • Members: Learn how to add and delete project members.
    • Volumes: Learn how to create and delete volumes, and how to check their details.
    • Notebooks: Learn how to create and delete Jupyter Lab Notebooks, and how to check their details.
    • Tensorboards: Learn how to create and delete Tensorboards, and how to check their details.
    • Model Registry: Learn how to view the list of models and check their details.
    • Pipelines interface
      • Pipelines preparations: Learn how to prepare to use the Pipelines feature.
      • Pipelines: Learn how to create and delete pipelines, and how to check their details.
      • Experiments: Learn how to create and delete experiments, and how to check their details.
      • Runs: Learn how to create and delete runs, and how to check their details.
      • Recurring runs: Learn how to create and delete recurring runs, and how to check their details.
    • Monitoring: Learn how to view the monitoring dashboard.
    • Train models using kubectl: Learn how to train models using kubectl.
    • Manage Secret using kubectl: Explains how to manage Secrets using kubectl.
• ML expert Platform permissions management: Manage accounts using NAVER Cloud Platform’s Sub Account.
• ML expert Platform release notes: See documentation updates.

ML expert Platform related resources

If you're considering ML expert Platform and need in-depth information for development, planning, or other purposes, these resources can help:

• Ncloud user environment guide: Explore VPC and Classic environments and supported services.
• Contact Support: Get help if you can't find what you need in the user guide.
• Sub Account user guide: Manage team access for ML expert Platform.