Machine Learning Based Crop Recommendation System

In a country where conventional farming methods are still widely used and often result in small yields and little profit for farmers, our goal is to increase crop yields by presenting a range of farming techniques through a recommendation system for intelligent farming. This system uses a scientific method to forecast the best crops depending on a number of important factors, such as the nutrients in the soil. It pinpoints nutritional deficits in the soil for particular crops. Our system, which is implemented as a website, makes use of crop dataset that include parameters for temperature, rainfall, pH, and humidity. It then applies a variety of ML algorithms to make accurate and efficient crop recommendations, achieving impressive metrics such as accuracy of 96.08%, precision of 93 %, and recall of 45%.