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Time series forecasting is a technique for the prediction of events through a sequence of time. Time-series forecasting decomposes the historical data into the baseline, trend, and seasonality. When a forecasting model doesn’t run as planned, we want to tune the parameters of the method with regards to the specific problem at hand. Tuning these methods requires a thorough understanding of how the underlying time series models work. A typical analyst/engineer will not know how to adjust these orders to avoid the problem. The Prophet package provides intuitive parameters which are easy to tune. Even someone like me who lacks expertise in forecasting models can use this to make meaningful predictions for a variety of problems in a business scenario.

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time-series-analysis fbprophet python facebook-prophet-forecasting

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