#0184

Cosine Similarity Between Vectors

MediumNumPy25 min20 XP

Problem

Given two NumPy vectors a and b, return their cosine similarity. Return 0.0 if either vector has zero norm.

Why This Matters

Cosine similarity is used for embeddings, document similarity, recommendation systems, and retrieval.

Function Signature

def cosine_similarity(a, b):

Examples

Example 1

Inputa = np.array([1, 0]), b = np.array([1, 1])

Output0.7071...

The dot product is 1 and the norms are 1 and sqrt(2).

Constraints

Return the exact requested result.
Handle common edge cases.
Keep the solution readable before optimizing.

CodePython

import numpy as np

def cosine_similarity(a, b):
    """
    Input example: a = np.array([1, 0]), b = np.array([1, 1])
    Return: 0.7071...
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return 0.0

import numpy as np

def cosine_similarity(a, b):
    """
    Input example: a = np.array([1, 0]), b = np.array([1, 1])
    Return: 0.7071...
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return 0.0

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Inputa = np.array([1, 0]), b = np.array([1, 1])

Expected0.7071...

The dot product is 1 and the norms are 1 and sqrt(2).

Hidden Test Categories

minimal inputrepeated valueslarger realistic input