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Unleashing the Power of Multiple Timeseries Forecasting ππ‘ Create forecasts with Stats & ML methods. Stats Methods with StatsForecast ML Methods with MLForecast Forecast plots Validate Modelβs Performance Plot CV Aggregate sales forecasts for all items Evaluate forecasts per store_item and CV window Distribution of errors Select Best Model Per Item_id & Cross Validation Fold We will find the perfect performing model per store_item (=item_id), evaluation metric & cross validation fold In what number of cross validation fold & metric is each model over performing best? What’s the perfect model for store_item=β1_1″ sales forecasting? Visualize the forecasts of the perfect model for unique_id == β1_1β Visualize AutoETS forecasts for more unique_ids Visualize XGBRegressor forecasts for more unique_ids Sources
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June 21, 2023
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