Customer analytics and segmentation project using K-Means clustering, EDA, and lookalike modeling. Assignment for Zeotap Data Scientist position. Analyzes 200 customers and 1,000 transactions with 5-cluster segmentation (DB Index: 1.05).

This repository contains a comprehensive data science project analyzing eCommerce transaction data, implementing customer segmentation, and developing a lookalike model. The project showcases EDA, clustering techniques, and recommendation systems using Python.

this is zeotap company project Software engineering internship