Agriculture has been the sector of paramount importance as it feeds the country's population along with contributing
to the GDP. Crop yield varies with a combination of factors including soil properties, climate, elevation and irrigation technique.
Technological developments have fallen short in estimating the yield based on this joint dependence of the said factors. Hence,
in this project a data-driven model that learns by historic soil as well as rainfall data to analyse and predict crop yield over
seasons in several districts, has been developed.
