Python RMSE Function | Dataford Interview Questions

Waabi evaluates prediction accuracy by comparing predicted driving values with observed values. Given two sequences, calculate their root mean square error (RMSE).

RMSE is defined as:

RMSE = sqrt(sum((predicted[i] - actual[i])²) / n)

Implement rmse(predicted, actual) and return the result as a floating-point number.

Formal Specification

Input: predicted, a non-empty list of numbers, and actual, a non-empty list of numbers.
Both lists have the same length n.
Output: A float representing the RMSE between corresponding values.
The input lists must not be modified.

Constraints

1 <= len(predicted) = len(actual) <= 10^5
Each value is an integer or floating-point number in [-10^9, 10^9]
The input lists are non-empty and have equal length
The input lists must not be modified

Function Signature

def rmse(predicted, actual):

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