Time Series Forecasting With Prophet
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Discover how Prophet, an open source library, accurately predicts power consumption in India for the next year. Learn to train and fit time series forecasting models, handling trends, seasonality, missing data, and outliers effectively. Benefit from its robustness and expertise in handling strong seasonal effects.
At a Glance
In this project, we will use the Prophet open source library to predict the power consumption in India for next year. Prophet is designed to automatically find a good set of hyperparameters for the model with skilful forecasts and data with trends and seasonal structure by default.
You can learn how to train and fit the time series forecasting model. Here we are using the model Prophet for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality along with holiday effects. It is also a robust way to handle missing data and shifts in the trend as well as handling outliers in the data. It works best with time series that have strong seasonal effects (Seasonality).
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