About
In many developing countries, agriculture is not only a predominant economic activity but also a vital source of sustenance and livelihood. However, these regions often face significant challenges due to inadequate weather forecasting systems and are highly vulnerable to climate-related adversities. Unlike developed countries, which have increasingly adopted Climate-Smart Agriculture (CSA) practices, developing nations have limited access to advanced technologies for managing weather risks. Hence, this project aims to utilise advanced machine learning techniques to improve weather prediction accuracy, specifically tailored for the agricultural needs of developing countries. The project seeks to assist farmers in making informed decisions to enhance crop yield and mitigate the risks of famine by providing more reliable weather forecasts.
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