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Beyond Machine Learning: Advantages of Ensemble Models for Interpretable Time Series Forecasting

Time series forecasting continues to be a critical task in many industries, including retail, finance, healthcare, and manufacturing. Traditional forecasting methods have been successful, but advancements in machine learning (ML) have sparked interest in using ML algorithms for time series forecasting. However, the complexity of exogenous events such as a pandemic and inclement weather, can make time series forecasting challenging.