Cosine Similarity Implementation | Dataford Interview Questions

Implement a function that computes the cosine similarity between two high-dimensional numeric vectors. Cosine similarity is defined as the dot product of the vectors divided by the product of their magnitudes.

Formal Specification

Write a function cosine_similarity(vec1, vec2) that takes two lists of numbers of equal length and returns a floating-point value.

If either vector has zero magnitude, return 0.0.
The vectors may contain positive, negative, or zero values.
Assume both inputs are valid Python lists of the same length.

Constraints

1 <= len(vec1) == len(vec2) <= 10^5
-10^9 <= vec1[i], vec2[i] <= 10^9
Vectors are the same length
Return 0.0 if either vector has zero magnitude

Function Signature

def cosine_similarity(vec1, vec2):

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