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This is the Summary report for the project made in this YouTube video: K-means clustering

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If you host your portfolio projects on GitHub, make sure you create README file in the format similar to below.

HR managers/recruiters most likely will not look through all your code, they are interested how you approach projects and deliver insights.

You project should have Objective/Goal, Methodology/Approach, Key Findings and Summary.

You can add the code used at the end of the file, so recruiters can review it if they want.

If you don’t want to create a portfolio on GitHub, you can create a Notion file (same as this one) and publish it as a web. Then add the link to this file to your CV and LinkedIn. It is Free.

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Mall Customer Segmentation Using K-Means Clustering

Objective

The goal of this project is to segment mall’s customers into distinct groups based on their annual income and spending behaviour. This segmentation can help in understanding customer profiles, which can be leveraged for targeted marketing strategies, product placements, and improving customer retention.

Methodology

I used K-Means clustering algorithm to segment the customers. The dataset consisted of customer demographics, including age, gender, annual income, and spending score.