:doc:`MachineLearning <../../machinelearning>` / Client / delete_ml_model

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delete_ml_model
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.. py:method:: MachineLearning.Client.delete_ml_model(**kwargs)

  

  Assigns the ``DELETED`` status to an ``MLModel``, rendering it unusable.

   

  After using the ``DeleteMLModel`` operation, you can use the ``GetMLModel`` operation to verify that the status of the ``MLModel`` changed to DELETED.

   

  **Caution:** The result of the ``DeleteMLModel`` operation is irreversible.

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/machinelearning-2014-12-12/DeleteMLModel>`_  


  **Request Syntax**
  ::

    response = client.delete_ml_model(
        MLModelId='string'
    )
    
  :type MLModelId: string
  :param MLModelId: **[REQUIRED]** 

    A user-supplied ID that uniquely identifies the ``MLModel``.

    

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

    
    ::

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

    

    - *(dict) --* 

      Represents the output of a ``DeleteMLModel`` operation.

       

      You can use the ``GetMLModel`` operation and check the value of the ``Status`` parameter to see whether an ``MLModel`` is marked as ``DELETED``.

      
      

      - **MLModelId** *(string) --* 

        A user-supplied ID that uniquely identifies the ``MLModel``. This value should be identical to the value of the ``MLModelID`` in the request.

        
  
  **Exceptions**
  
  *   :py:class:`MachineLearning.Client.exceptions.InvalidInputException`

  
  *   :py:class:`MachineLearning.Client.exceptions.ResourceNotFoundException`

  
  *   :py:class:`MachineLearning.Client.exceptions.InternalServerException`

  