/Gasoline-Demand-Forecasting

Explored patterns, trends, and seasonality of US gasoline demand data. Compared models based on the mean squared error of the testing set. Employed ARIMA, XGBoost, Facebook Prophet, and Recurrent Neural Network to forecast future gasoline demand

Primary LanguageJupyter Notebook

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