Ganga-R-1343/Meditrak-Demand-Forecasting

Predictive inventory analytics & multi-store demand forecasting system for retail pharmacy networks using Random Forest regression and Streamlit. # Meditrak-Demand-Forecasting # 💊 Meditrak: Multi-Store Demand Forecasting & Inventory Optimization **Meditrak** is a machine learning solution for retail pharmacy chains to prevent stockouts of critical medications, minimize drug expiration waste, and optimize safety stock levels across global branches. --- ## ✨ Features * **🔮 Real-Time Demand Prediction:** Projects unit sales per product line across store locations using a Random Forest Regressor. * **🛡️ Dynamic Safety Stock Buffers:** Automatically calculates safety stock ($20\%$ buffer) to prevent stockouts. * **📋 Smart Reorder Targets:** Generates purchase order quantities using: $$\text{Reorder Target} = \text{Predicted Demand} + \text{Safety Stock}$$ * **📊 Regional Analytics:** Visualizes demand trends across drug categories and store locations. --- ## 🚀 Quick Start Guide ### 1. Clone the Repository ```bash git clone github.com cd Meditrak-Demand-Forecasting 📊 Model Performance MetricsMetricScoreMAE (Mean Absolute Error)~2.15 unitsMSE (Mean Squared Error)~7.80 unitsRMSE (Root Mean Squared Error)~2.79 units$R^2$ Score~0.91