Day 5— Cosine Similarity🧠

This series is going to be a one stop solution for learning a new topic everyday.

Topic : Cosine Similarity

• When 2 phrases has nothing in common then Cosine Similarity score is 0 (cos 90 = 0)
• When 2 phases are exactly same then Cosine Similarity score is 1 (Cos 0 = 1)
• When there are some overlap between the 2 phrases then Cosine Similarity score is between 0 and 1 (Cos 0 — Cos 90)

Example :

We compute the dot product of the occurrence vectors, and divide by the product of their magnitudes

• Numerator is the dot product of the two vectors.
• Denominator are the magnitudes of each vector.

Article Source :

• Cosine similarity
• Understanding Vector Similarity for Machine Learning
• Cosine Similarity, Clearly Explained!!!

TL;DR :

Cosine similarity is a measure of the angle between two vectors in a multi-dimensional space. It determines how similar two vectors are in terms of their direction, ignoring their magnitude or length. The closer the angle is to 0 degrees (or 0 radians), the more similar the vectors are, and the similarity is measured by the cosine of that angle.

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