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Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model.
The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant.
When you use SageMaker Studio or the SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the Amazon Web Services SDK for Python (Boto), you must use the logging APIs provided by the SDK.
You can add tags to experiments, trials, trial components and then use the Search API to search for the tags.
To add a description to an experiment, specify the optional
parameter. To add a description later, or to change the description, call the UpdateExperiment
To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.
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 BeginCreateExperiment and EndCreateExperiment.
public virtual Task<CreateExperimentResponse> CreateExperimentAsync( CreateExperimentRequest request, CancellationToken cancellationToken )
Container for the necessary parameters to execute the CreateExperiment service method.
A cancellation token that can be used by other objects or threads to receive notice of cancellation.
|ResourceLimitExceededException||You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.|
.NET Core App:
Supported in: 3.1
Supported in: 2.0
Supported in: 4.5