Student seeks advice on global vs. separate models for multi-location demand forecasting

A B.Tech student is seeking advice on building a demand forecasting agent for a supply chain optimization project. The student is working with a synthetic dataset of 1.1 million records across 40 locations and needs to decide between training 40 separate models or a single global model. Key concerns include the global model's ability to capture location-specific demand patterns and potential issues with averaging regional trends. The student is also exploring hybrid approaches and seeking recommendations for suitable forecasting models and validation strategies to ensure accurate, location-specific predictions. AI

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RANK_REASON User is asking for advice on a technical ML problem, not reporting on a new development.

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• 1.1 million records
• 40 locations
• CSE (AI/ML)
• demand forecasting
• Demand Forecasting Agent
• global model
• separate models
• supply chain optimization
• synthetic retail supply chain dataset

• product
• other

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