sagemaker_create_project: Creates a machine learning (ML) project that can contain one...

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

Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model

Description

Creates a machine learning (ML) project that can contain one or more templates that set up an ML pipeline from training to deploying an approved model.

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

Usage

sagemaker_create_project(
  ProjectName,
  ProjectDescription = NULL,
  ServiceCatalogProvisioningDetails,
  Tags = NULL
)

Arguments

ProjectName	[required] The name of the project.
ProjectDescription	A description for the project.
ServiceCatalogProvisioningDetails	[required] 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 that you want to use to organize and track your Amazon Web Services resource costs. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.