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Cosine Similarity in Python - TAE

Finding the cosine of the angle between two non-zero vectors is the fundamental concept of cosine similarity. The cosine of the angle equals one if the vectors are identical, signifying perfect matching. The cosine of zero indicates no similarity if the vectors are orthogonal or perpendicular. Cosine similarity has a range of -1 to 1.

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Cosine Similarity in Python - TAE

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  1. COSINE SIMILARITY IN PYTHON www.tutorialandexample.com

  2. WHAT IS COSINE SIMILARITY IN PYTHON The fundamental concept of cosine similarity is the cosine of the angle between two non-zero vectors. If the vectors are identical, the cosine of the angle equals one, signifying perfect matching. If the vectors are orthogonal or perpendicular, the cosine of zero indicates no similarity. Cosine similarity has a range of -1 to 1.

  3. MATHEMATICAL FORMULA The following formula is used to determine the cosine similarity between two vectors, A and B: Cosine_Similarity = (A.B)/(||A||.||B||)

  4. PYTHON IMPLEMENTATION: Let's implement cosine similarity in Python using the numpy library: Code:

  5. import numpy as np def cosine_similarity(vector_a, vector_b): dot_product = np.dot(vector_a, vector_b) norm_a = np.linalg.norm(vector_a) norm_b = np.linalg.norm(vector_b) similarity = dot_product / (norm_a * norm_b) return similarity vector1 = np.array([1, 2, 3]) vector2 = np.array([4, 5, 6]) similarity_score = cosine_similarity(vector1, vector2) print(f"Cosine Similarity: {similarity_score}")

  6. Output Cosine Similarity: 0.9746318461970762 This example shows how to use numpy to implement cosine similarity in Python simply.

  7. THANK +91 9599321147 YOU! www.tutorialandexample.com

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