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Final 3993 by Ly Lê is a document available to read on EtoBox.

This research article presents a machine learning framework for retail sales forecasting developed for SuperKart, a multi-city retail chain. The framework integrates data preprocessing, exploratory data analysis, feature engineering, and model evaluation, with XGBoost identified as the most effective algorithm achieving an R² score of 0.87. Additionally, a low-code deployment strategy was implemented to enable business users to generate real-time forecasts with minimal technical intervention.

Author
Ly Lê
Language
EN