ABSTRACT
A significant problem in the realm of agricultural endeavor is yield prediction. Anyone involved in agriculture (a farmer) is curious to know how much produce is too expected. Years back, yield output prediction Were Made based on farmers’ prior experiences. Considering the information at hand, the yield forecast is a significant problem that has to be resolved. Techniques for machine learning are one method to overcome that problem. Agriculture uses a variety of Machine Learning (ML) algorithm to Jude the crop production for following year and evaluates their performance. Based on previously gathered data, a system to estimate crop output is proposed and put into practice in this work. The purpose of this research is to develop a prediction model to be used to predict the future of agriculture. It briefly explains how machine learning can be used to predict agricultural yield.
