Forecasting time series data using Facebook Prophet
The Prophet library is a popular open source project that was originally developed at Facebook (Meta) based on a 2017 paper that proposed an algorithm for time series forecasting titled Forecasting at Scale. The project soon gained popularity due to its simplicity, its ability to create compelling and performant forecasting models, and its ability to handle complex seasonality, holiday effects, missing data, and outliers. The Prophet library automates many aspects of designing a forecasting model while providing additional out-of-the-box visualizations. The library offers additional capabilities, such as building growth models (saturated forecasts), working with uncertainty in trend and seasonality, and changepoint detection.
In this recipe, you will use the Milk Production dataset used in the previous recipe. This will help you understand the different forecasting approaches while using the same dataset for benchmarking.
The...
