What does the @ mean in this equation?

Asked Nov 05 '18 at 19:32

Active Nov 05 '18 at 19:32

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I am seeing this equation for computing the cosine similarity of a vector and a matrix in a post.

The numerator of cos similarity can be expressed as a matrix multiply and then the denominator should just work :).

    a_norm = np.linalg.norm(a, axis=1)
    b_norm = np.linalg.norm(b)
    (a @ b) / (a_norm * b_norm)
    where a is a 2D array and b is 1D array (i.e. vector)

What does the (a @ b) mean? How to compute this in numpy?

asked Nov 05 '18 at 19:32

user697911

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Use `numpy.matmul`. – Divakar Nov 05 '18 at 19:33
Particularly [this](https://stackoverflow.com/a/46027116/2285236) answer. – ayhan Nov 05 '18 at 19:35
Did you read the comment you pasted? hint: "The numerator of cos similarity can be expressed as a **matrix multiply** ..." – Matt Messersmith Nov 05 '18 at 19:36

What does the @ mean in this equation?

0 Answers0