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- Forecasting at scale. - Prophet
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects It works best with time series that have strong seasonal effects and several seasons of historical data
- Quick Start - Prophet
Prophet is a forecasting procedure implemented in R and Python It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts
- Installation - Prophet
Prophet has two implementations: R and Python Installation in R Prophet is a CRAN package so you can use install packages
- Trend Changepoints - Prophet
Automatic changepoint detection in Prophet Prophet detects changepoints by first specifying a large number of potential changepoints at which the rate is allowed to change
- Diagnostics - Prophet
Prophet is a forecasting procedure implemented in R and Python It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts
- Non-Daily Data - Prophet
Prophet is a forecasting procedure implemented in R and Python It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts
- Uncertainty Intervals - Prophet
The biggest source of uncertainty in the forecast is the potential for future trend changes The time series we have seen already in this documentation show clear trend changes in the history Prophet is able to detect and fit these, but what trend changes should we expect moving forward?
- Seasonality, Holiday Effects, And Regressors | Prophet
Prophet is a forecasting procedure implemented in R and Python It is fast and provides completely automated forecasts that can be tuned by hand by data scientists and analysts
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