VN2 Inventory Planning Challenge
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Test your inventory planning skills: cut holding costs, prevent shortages, and master real-world inventory planning.
This notebook demonstrates the use of StatsForecast and NeuralForecast methods to analyze time series data. It includes the methodology to identify the demand type of each time series, helping to understand patterns such as intermittent, smooth, or seasonal demand.
This notebook demonstrates how to use StatsForecast and NeuralForecast methods to analyze and forecast time series data. It focuses on understanding the type of demand for each series—whether it is intermittent, smooth, or lumpy. By combining statistical and neural forecasting approaches, the notebook helps uncover patterns in the data, evaluate forecast accuracy, and generate actionable insights.
The goal is to provide a practical framework for improving demand predictions, guiding model selection, and supporting data-driven decision-making in forecasting and inventory planning.
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