Many Al algorithms rely on repeatedly calculating the distance between two points For instance, if we want to classify photos together, we would want the items in the same class to have a smaller distance between therm One of the most common distance tool for the job is the Euclidean Distance. It can apply to n dimensional spaces and is fast to calculate. More more info, see the Wiki article Below is the relevant equation that calculate the distance between two n-dimensional points: p, q i-l Use a for loop on NumPy arays for the following function. In [ J: def edfor(p, q Implement Euclidean Distance using a for loop Expects 2 np.arrays as input Returns their distance # YOUR CODE HERE raise NotImplementedError) Expected output: edfor([3,4], [e,e]) yields 5