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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.
For .NET Core this operation is only available in asynchronous form. Please refer to CreateExperimentAsync.
public virtual CreateExperimentResponse CreateExperiment( CreateExperimentRequest request )
Container for the necessary parameters to execute the CreateExperiment service method.
|ResourceLimitExceededException||You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.|
Supported in: 4.5, 4.0, 3.5