AWS services or capabilities described in AWS Documentation may vary by region/location. Click Getting Started with Amazon AWS to see specific differences applicable to the China (Beijing) Region.
Creates an SageMaker AI notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
In a CreateNotebookInstance
request, specify the type of ML compute instance
that you want to run. SageMaker AI launches the instance, installs common libraries
that you can use to explore datasets for model training, and attaches an ML storage
volume to the notebook instance.
SageMaker AI also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker AI with a specific algorithm or with a machine learning framework.
After receiving the request, SageMaker AI does the following:
Creates a network interface in the SageMaker AI VPC.
(Option) If you specified SubnetId
, SageMaker AI creates a network interface
in your own VPC, which is inferred from the subnet ID that you provide in the input.
When creating this network interface, SageMaker AI attaches the security group that
you specified in the request to the network interface that it creates in your VPC.
Launches an EC2 instance of the type specified in the request in the SageMaker AI
VPC. If you specified SubnetId
of your VPC, SageMaker AI specifies both network
interfaces when launching this instance. This enables inbound traffic from your own
VPC to the notebook instance, assuming that the security groups allow it.
After creating the notebook instance, SageMaker AI returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.
After SageMaker AI creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker AI endpoints, and validate hosted models.
For more information, see How It Works.
This is an asynchronous operation using the standard naming convention for .NET 4.5 or higher. For .NET 3.5 the operation is implemented as a pair of methods using the standard naming convention of BeginCreateNotebookInstance and EndCreateNotebookInstance.
Namespace: Amazon.SageMaker
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public abstract Task<CreateNotebookInstanceResponse> CreateNotebookInstanceAsync( CreateNotebookInstanceRequest request, CancellationToken cancellationToken )
Container for the necessary parameters to execute the CreateNotebookInstance service method.
A cancellation token that can be used by other objects or threads to receive notice of cancellation.
Exception | Condition |
---|---|
ResourceLimitExceededException | You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. |
.NET:
Supported in: 8.0 and newer, Core 3.1
.NET Standard:
Supported in: 2.0
.NET Framework:
Supported in: 4.5 and newer