A Framework for Multi-Model Forecasting on Databricks

Time series forecasting is crucial for inventory and demand management. The Many Model Forecasting (MMF) framework on Databricks aims to improve forecast accuracy by allowing businesses to train and predict using multiple models at scale. MMF supports data preparation, backtesting, cross-validation, scoring, and deployment with over 40 integrated models. It minimizes coding efforts, enabling teams to focus on evaluation and deployment, supporting seamless utilization within Databricks' ecosystem. The framework emphasizes automated logging, fine-grained access control, and optimal model management through integration with Databricks Mosaic AI and MLflow.