Abstract
Abstract: As early as the Indus Valley Civilization Era, agriculture in India is recorded. The agriculture industry provides employment in developing countries such as India and is considered the backbone of the economy. The benefit of machine learning in farming is that it provides farmers with proper recommendations and judgments about crops. By applying machine learning to agriculture, farmers can increase efficiency, quality production, precision, and while consuming minimum human effort. This research work focused on applying various Machine Learning techniques for predicting the yield of the crop for the various districts of Bihar agricultural dataset. Here we used Random Forest, Decision Tree, SVR, XGBregressor, and Deep Neural Network for the prediction of crop yield, and their comparisons are made on the basis of MAE. This work will help farmers in predicting the yield of various crops based on past data. Therefore, farmers can select crops that suffer the fewest losses by using this tool.
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