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Weather forecasting has traditionally been done by complex simulation models of physics made up of complex equations of fluid dynamics and thermodynamics. Due to this, even minute errors in the simulation causes huge differences in the results. Thus, this method is inaccurate for long-term forecasting. On the other hand, machine learning techniques are more robust to minute errors in training datasets. In this paper we explore machine learning regression algorithm application to weatherdoi:10.33564/ijeast.2020.v05i06.022 fatcat:hl5mdegrenathfsjrfpo72izee