Data Science - Time Series Forecasting with Facebook Prophet in Python - Forecasting Metrics

The video tutorial covers various error metrics used in time series analysis, including the sum of squared errors, mean squared error, root mean squared error, and mean absolute error. It explains the advantages and disadvantages of each metric, particularly in terms of scale and interpretability. The tutorial also introduces scale invariant metrics like R-squared and percentage error metrics such as MAPE and SMAPE, highlighting their uses and limitations. The goal is to familiarize viewers with these metrics to enhance their understanding and application in real-world scenarios.

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