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Container for the parameters to the CreateNotebookInstance operation. Creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.
CreateNotebookInstance request, specify the type of ML compute instance
that you want to run. Amazon SageMaker 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.
Amazon SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use Amazon SageMaker with a specific algorithm or with a machine learning framework.
After receiving the request, Amazon SageMaker does the following:
Creates a network interface in the Amazon SageMaker VPC.
(Option) If you specified
SubnetId, Amazon SageMaker 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, Amazon SageMaker attaches the security
group that you specified in the request to the network interface that it creates in
Launches an EC2 instance of the type specified in the request in the Amazon SageMaker
VPC. If you specified
SubnetId of your VPC, Amazon SageMaker 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
After creating the notebook instance, Amazon SageMaker returns its Amazon Resource Name (ARN).
After Amazon SageMaker 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 Amazon SageMaker endpoints, and validate hosted models.
For more information, see How It Works.
public class CreateNotebookInstanceRequest : AmazonSageMakerRequest IAmazonWebServiceRequest
The CreateNotebookInstanceRequest type exposes the following members
Gets and sets the property DirectInternetAccess.
Sets whether Amazon SageMaker provides internet access to the notebook instance. If
you set this to
For more information, see appendix-notebook-and-internet-access. You can set
the value of this parameter to
Gets and sets the property InstanceType.
The type of ML compute instance to launch for the notebook instance.
Gets and sets the property KmsKeyId.
If you provide a AWS KMS key ID, Amazon SageMaker uses it to encrypt data at rest on the ML storage volume that is attached to your notebook instance.
Gets and sets the property LifecycleConfigName.
The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see notebook-lifecycle-config.
Gets and sets the property NotebookInstanceName.
The name of the new notebook instance.
Gets and sets the property RoleArn.
When you send any requests to AWS resources from the notebook instance, Amazon SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so Amazon SageMaker can perform these tasks. The policy must allow the Amazon SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see Amazon SageMaker Roles.
To be able to pass this role to Amazon SageMaker, the caller of this API must have
Gets and sets the property SecurityGroupIds.
The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
Gets and sets the property SubnetId.
The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
Gets and sets the property Tags.
A list of tags to associate with the notebook instance. You can add tags later by
Supported in: 1.3
Supported in: 4.5, 4.0, 3.5
Portable Class Library:
Supported in: Windows Store Apps
Supported in: Windows Phone 8.1
Supported in: Xamarin Android
Supported in: Xamarin iOS (Unified)
Supported in: Xamarin.Forms