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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def rmse(targets, predictions):
 r""" Compute the root mean squared error between two SArrays. Parameters targets : SArray[float or int] An Sarray of ground truth target values. predictions : SArray[float or int] The prediction that corresponds to each target value. This vector must have the same length as ``targets``. Returns ------- out : float The RMSE between the two SArrays. See Also -------- max_error Notes ----- The root mean squared error between two vectors, x and y, is defined as: .. math:: RMSE = \sqrt{\frac{1}{N} \sum_{i=1}^N (x_i - y_i)^2} References - `Wikipedia - root-mean-square deviation <http://en.wikipedia.org/wiki/Root-mean-square_deviation>`_ Examples -------- 1.2749117616525465 """


    _supervised_evaluation_error_checking(targets, predictions)
    return _turicreate.extensions._supervised_streaming_evaluator(targets,
                                       predictions, "rmse", {})