Presentation: Forecasting with Prophet
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Abstract
Forecasting is a common data science task that helps organizations with capacity planning, goal setting, and anomaly detection. Despite its importance, there are serious challenges associated with producing reliable and high quality forecasts – especially when there are a variety of time series and analysts with expertise in time series modeling are relatively rare. To address these challenges, we describe a practical, modular approach to forecasting “at scale” based on a flexible curve fitting procedure that produces high quality forecasts across a wide variety of business time series.
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