:doc:`SageMaker <../../sagemaker>` / Client / create_experiment

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create_experiment
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.. py:method:: SageMaker.Client.create_experiment(**kwargs)

  

  Creates a 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.

   

  .. note::

    

    In the Studio UI, trials are referred to as *run groups* and trial components are referred to as *runs*.

    

   

  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 <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html>`__ API to search for the tags.

   

  To add a description to an experiment, specify the optional ``Description`` parameter. To add a description later, or to change the description, call the `UpdateExperiment <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateExperiment.html>`__ API.

   

  To get a list of all your experiments, call the `ListExperiments <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListExperiments.html>`__ API. To view an experiment's properties, call the `DescribeExperiment <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeExperiment.html>`__ API. To get a list of all the trials associated with an experiment, call the `ListTrials <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTrials.html>`__ API. To create a trial call the `CreateTrial <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrial.html>`__ API.

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperiment>`_  


  **Request Syntax**
  ::

    response = client.create_experiment(
        ExperimentName='string',
        DisplayName='string',
        Description='string',
        Tags=[
            {
                'Key': 'string',
                'Value': 'string'
            },
        ]
    )
    
  :type ExperimentName: string
  :param ExperimentName: **[REQUIRED]** 

    The name of the experiment. The name must be unique in your Amazon Web Services account and is not case-sensitive.

    

  
  :type DisplayName: string
  :param DisplayName: 

    The name of the experiment as displayed. The name doesn't need to be unique. If you don't specify ``DisplayName``, the value in ``ExperimentName`` is displayed.

    

  
  :type Description: string
  :param Description: 

    The description of the experiment.

    

  
  :type Tags: list
  :param Tags: 

    A list of tags to associate with the experiment. You can use `Search <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html>`__ API to search on the tags.

    

  
    - *(dict) --* 

      A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

       

      You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see `AddTags <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AddTags.html>`__.

       

      For more information on adding metadata to your Amazon Web Services resources with tagging, see `Tagging Amazon Web Services resources <https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html>`__. For advice on best practices for managing Amazon Web Services resources with tagging, see `Tagging Best Practices\: Implement an Effective Amazon Web Services Resource Tagging Strategy <https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf>`__.

      

    
      - **Key** *(string) --* **[REQUIRED]** 

        The tag key. Tag keys must be unique per resource.

        

      
      - **Value** *(string) --* **[REQUIRED]** 

        The tag value.

        

      
    

  
  :rtype: dict
  :returns: 
    
    **Response Syntax**

    
    ::

      {
          'ExperimentArn': 'string'
      }
      
    **Response Structure**

    

    - *(dict) --* 
      

      - **ExperimentArn** *(string) --* 

        The Amazon Resource Name (ARN) of the experiment.

        
  
  **Exceptions**
  
  *   :py:class:`SageMaker.Client.exceptions.ResourceLimitExceeded`

  