sagemaker_update_project: Updates a machine learning (ML) project that is created from...

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model

Description

Updates a machine learning (ML) project that is created from a template that sets up an ML pipeline from training to deploying an approved model.

See https://www.paws-r-sdk.com/docs/sagemaker_update_project/ for full documentation.

Usage

sagemaker_update_project(
  ProjectName,
  ProjectDescription = NULL,
  ServiceCatalogProvisioningUpdateDetails = NULL,
  Tags = NULL
)

Arguments

ProjectName	[required] The name of the project.
ProjectDescription	The description for the project.
ServiceCatalogProvisioningUpdateDetails	The product ID and provisioning artifact ID to provision a service catalog. The provisioning artifact ID will default to the latest provisioning artifact ID of the product, if you don't provide the provisioning artifact ID. For more information, see What is Amazon Web Services Service Catalog.
Tags	An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources. In addition, the project must have tag update constraints set in order to include this parameter in the request. For more information, see Amazon Web Services Service Catalog Tag Update Constraints.

paws.machine.learning documentation built on Sept. 12, 2023, 1:14 a.m.