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This project aims to analyze and forecast daily revenue and the daily number of receipts across six distinct restaurants, by employing a statistical approach and utilizing predictive models, particularly the SARIMA and TBATS models.
A comparative breakdown of traditional econometric timeseries models vs. more modern ML methods for predicting a retail firm's sales over a short to medium horizon
Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements