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Understanding Embeddings
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Understanding Embeddings
Question 1 of 4
25%
Why is cosine similarity preferred over Euclidean distance for comparing embeddings?
A
It is faster to compute
B
It measures the angle (direction of meaning) rather than magnitude, making it more robust
C
It returns values between 0 and 1, which is easier to interpret
D
It is the only metric that vector databases support
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