The future of India's citizens' well-being depends heavily on agricultural practices. Machine learning can be used to make important decisions that will help ensure a sustainable food supply and keep farmers up-to-date with the latest weather patterns. In a recent study, researchers examined the use of artificial intelligence techniques to identify crop yield prediction models and Supervised learning, a commonly used technique for grading fruits, was unable to account for the nonlinear relationship between input variables and output variables. Although these techniques allow for greater accuracy in predicting crop yield, they come with a high price tag. A growing number of studies have found that ML techniques can be used to estimate crop yield. This paper explores how well these techniques work in practice, by providing a detailed analysis of their accuracy.
Software And Hardware