Applied Machine Learning for Predicting Crop Performance: A Supervised Learning Perspective

Agriculture is fraught with uncertainty due to climate change, rainfall, soil types, and many other factors. Crop prediction in agriculture is a major dilemma and there are huge data sets where farmers struggle to predict the right seed. In this situation of population growth, it is necessary to increase the production of crops and agricultural products at the same time in order to meet people's needs. These problems can be solved with machine learning algorithms. This white paper focuses on those solutions. Real-time environmental parameters such as soil type, precipitation, humidity, and past weather are recorded for the Tamil Nadu district, and ANN algorithms are used for crop prediction and accuracy