The Prophet model, developed by Meta, is an open-source forecasting tool for time series data, particularly effective for data exhibiting strong seasonality and trends. It uses a piecewise-linear or logistic growth trend, Fourier series for seasonality, and incorporates holidays for adjustments in forecasts. Implementing Prophet in Python requires two key features from the Pandas DataFrame: the date stamp ("ds") and the target variable ("y"). Unlike models like ARIMA, Prophet handles non-stationary data efficiently. Adding holidays as dummy variables enhances predictive accuracy by accounting for historical events that cause deviations. Despite complexity, Prophet forecasts offer a comprehensive view through automated predictions and confidence intervals.

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