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A forecasting model to predict bottled Zamzam water demand based on weather, time, and pilgrim statistics.
<p>Developed as part of a machine learning coursework, this project uses linear regression to forecast the required number of bottled Zamzam water units at distribution points in Makkah. It considers variables such as temperature, time of day, and number of pilgrims. The project includes data preprocessing, feature engineering, and model evaluation to support accurate, data-driven decisions for resource allocation.</p><div><br></div>
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