Automated Demand Forecasting and Order Optimization System for Franchise Retail Chains
Design an integrated system that leverages machine learning to forecast demand per store, and generate optimized daily order recommendations using real-time and historical data inputs, including local store factors, sales trends, promotions, weather, and location-specific parameters. The system should present clear, actionable insights through an intuitive user interface, supporting quick decision-making and seamless operational workflow.
Machine learning frameworks such as TensorFlow or PyTorch for demand modeling, Cloud-based deployment for scalability and flexibility, Data pipelines supporting real-time data ingestion and processing...