code: @Override
      public CreateHyperParameterTuningJobResult createHyperParameterTuningJob(CreateHyperParameterTuningJobRequest request) {
          request = beforeClientExecution(request);
          return executeCreateHyperParameterTuningJob(request);
      }
docs: <p>
  Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many
  training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that
  you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured
  by an objective metric that you choose.
  </p>
  
  @param createHyperParameterTuningJobRequest
  @return Result of the CreateHyperParameterTuningJob operation returned by the service.
  @throws ResourceInUseException
  Resource being accessed is in use.
  @throws ResourceLimitExceededException
  You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs
  created.
  @sample AmazonSageMaker.CreateHyperParameterTuningJob
  @see <a href="http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJob"
  target="_top">AWS API Documentation</a>