code: @Override
      public CreateModelResult createModel(CreateModelRequest request) {
          request = beforeClientExecution(request);
          return executeCreateModel(request);
      }
docs: <p>
  Creates a model in Amazon SageMaker. In the request, you name the model and describe a primary container. For the
  primary container, you specify the docker image containing inference code, artifacts (from prior training), and
  custom environment map that the inference code uses when you deploy the model for predictions.
  </p>
  <p>
  Use this API to create a model if you want to use Amazon SageMaker hosting services or run a batch transform job.
  </p>
  <p>
  To host your model, you create an endpoint configuration with the <code>CreateEndpointConfig</code> API, and then
  create an endpoint with the <code>CreateEndpoint</code> API. Amazon SageMaker then deploys all of the containers
  that you defined for the model in the hosting environment.
  </p>
  <p>
  To run a batch transform using your model, you start a job with the <code>CreateTransformJob</code> API. Amazon
  SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location.
  </p>
  <p>
  In the <code>CreateModel</code> request, you must define a container with the <code>PrimaryContainer</code>
  parameter.
  </p>
  <p>
  In the request, you also provide an IAM role that Amazon SageMaker can assume to access model artifacts and
  docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also
  use the IAM role to manage permissions the inference code needs. For example, if the inference code access any
  other AWS resources, you grant necessary permissions via this role.
  </p>
  
  @param createModelRequest
  @return Result of the CreateModel operation returned by the service.
  @throws ResourceLimitExceededException
  You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs
  created.
  @sample AmazonSageMaker.CreateModel
  @see <a href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModel" target="_top">AWS API
  Documentation</a>