This repository provides a Python implementation of K-Means clustering for segmenting retail store customers based on their purchase behavior. The algorithm groups customers into clusters using features such as Annual Income and Spending Score, enabling data-driven decision-making for marketing strategies.
Prediction of optimal number of clusters of the given iris data and it's visualisation.
ML Engineering, AI & Data Science: student at Lambda School. Prev B2C Growth & Storytelling via Motion Picture & Still Photography
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