def describe_ml_models(FilterVariable=None, EQ=None, GT=None, LT=None, GE=
    None, LE=None, NE=None, Prefix=None, SortOrder=None, NextToken=None,
    Limit=None):
    """
    Returns a list of MLModel that match the search criteria in the request.
    See also: AWS API Documentation
    
    
    :example: response = client.describe_ml_models(
        FilterVariable='CreatedAt'|'LastUpdatedAt'|'Status'|'Name'|'IAMUser'|'TrainingDataSourceId'|'RealtimeEndpointStatus'|'MLModelType'|'Algorithm'|'TrainingDataURI',
        EQ='string',
        GT='string',
        LT='string',
        GE='string',
        LE='string',
        NE='string',
        Prefix='string',
        SortOrder='asc'|'dsc',
        NextToken='string',
        Limit=123
    )
    
    
    :type FilterVariable: string
    :param FilterVariable: Use one of the following variables to filter a list of MLModel :
            CreatedAt - Sets the search criteria to MLModel creation date.
            Status - Sets the search criteria to MLModel status.
            Name - Sets the search criteria to the contents of MLModel **** Name .
            IAMUser - Sets the search criteria to the user account that invoked the MLModel creation.
            TrainingDataSourceId - Sets the search criteria to the DataSource used to train one or more MLModel .
            RealtimeEndpointStatus - Sets the search criteria to the MLModel real-time endpoint status.
            MLModelType - Sets the search criteria to MLModel type: binary, regression, or multi-class.
            Algorithm - Sets the search criteria to the algorithm that the MLModel uses.
            TrainingDataURI - Sets the search criteria to the data file(s) used in training a MLModel . The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.
            

    :type EQ: string
    :param EQ: The equal to operator. The MLModel results will have FilterVariable values that exactly match the value specified with EQ .

    :type GT: string
    :param GT: The greater than operator. The MLModel results will have FilterVariable values that are greater than the value specified with GT .

    :type LT: string
    :param LT: The less than operator. The MLModel results will have FilterVariable values that are less than the value specified with LT .

    :type GE: string
    :param GE: The greater than or equal to operator. The MLModel results will have FilterVariable values that are greater than or equal to the value specified with GE .

    :type LE: string
    :param LE: The less than or equal to operator. The MLModel results will have FilterVariable values that are less than or equal to the value specified with LE .

    :type NE: string
    :param NE: The not equal to operator. The MLModel results will have FilterVariable values not equal to the value specified with NE .

    :type Prefix: string
    :param Prefix: A string that is found at the beginning of a variable, such as Name or Id .
            For example, an MLModel could have the Name 2014-09-09-HolidayGiftMailer . To search for this MLModel , select Name for the FilterVariable and any of the following strings for the Prefix :
            2014-09
            2014-09-09
            2014-09-09-Holiday
            

    :type SortOrder: string
    :param SortOrder: A two-value parameter that determines the sequence of the resulting list of MLModel .
            asc - Arranges the list in ascending order (A-Z, 0-9).
            dsc - Arranges the list in descending order (Z-A, 9-0).
            Results are sorted by FilterVariable .
            

    :type NextToken: string
    :param NextToken: The ID of the page in the paginated results.

    :type Limit: integer
    :param Limit: The number of pages of information to include in the result. The range of acceptable values is 1 through 100 . The default value is 100 .

    :rtype: dict
    :return: {
        'Results': [
            {
                'MLModelId': 'string',
                'TrainingDataSourceId': 'string',
                'CreatedByIamUser': 'string',
                'CreatedAt': datetime(2015, 1, 1),
                'LastUpdatedAt': datetime(2015, 1, 1),
                'Name': 'string',
                'Status': 'PENDING'|'INPROGRESS'|'FAILED'|'COMPLETED'|'DELETED',
                'SizeInBytes': 123,
                'EndpointInfo': {
                    'PeakRequestsPerSecond': 123,
                    'CreatedAt': datetime(2015, 1, 1),
                    'EndpointUrl': 'string',
                    'EndpointStatus': 'NONE'|'READY'|'UPDATING'|'FAILED'
                },
                'TrainingParameters': {
                    'string': 'string'
                },
                'InputDataLocationS3': 'string',
                'Algorithm': 'sgd',
                'MLModelType': 'REGRESSION'|'BINARY'|'MULTICLASS',
                'ScoreThreshold': ...,
                'ScoreThresholdLastUpdatedAt': datetime(2015, 1, 1),
                'Message': 'string',
                'ComputeTime': 123,
                'FinishedAt': datetime(2015, 1, 1),
                'StartedAt': datetime(2015, 1, 1)
            },
        ],
        'NextToken': 'string'
    }
    
    
    :returns: 
    PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an MLModel .
    INPROGRESS - The creation process is underway.
    FAILED - The request to create an MLModel didn't run to completion. The model isn't usable.
    COMPLETED - The creation process completed successfully.
    DELETED - The MLModel is marked as deleted. It isn't usable.
    
    """
    pass
