Rossmann Retail Sales Prediction
End-to-end ML pipeline forecasting daily retail sales on the Rossmann Store Sales dataset (1M records, 1,115 stores). Compares Linear Regression, Random Forest, and XGBoost with time-series cross-validation. Tuned XGBoost achieves R² = 0.89 on a 6-week-ahead test window.
Rossmann product price extractor
Time series sales forecasting — Prophet vs LightGBM on Rossmann dataset. MAPE 9.47%. Deployed on Streamlit Cloud.
Rossmann store sales forecasting: Prophet vs SARIMA vs LightGBM. MAPE 8.20% (LightGBM winner, 2x better than classical models). Walk-forward CV + anomaly detection on 1M rows.
DEPI team project predicting Rossmann store sales — EDA, feature engineering, and an ML pipeline tuned with GridSearchCV (final XGBoost model: 97.9% R2). Deployed via Streamlit, FastAPI, and Power BI.
Time series sales forecast for Rossmann Pharmaceuticals
🏪 The project's idea is to use a machine learning model to predict the sales quantity that each store will have in the next six weeks, assisting managers in their future decision-making.
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