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The linked article is about different strategies for building predictive models from historical data. The post describes time series forecasting, regression analysis, and time series forecasting with covariates. The article also discusses different techniques such as SMA, EMA, and ARIMA, which are commonly used for time series forecasting. Additionally, the article explains the importance of feature engineering and provides examples of adding independent variables to enhance forecasting models. Finally, the article mentions Facebook Prophet and deep learning models as other techniques and suggests using ensemble approaches to improve accuracy.