Crop And Fertilizer Recommendation System

Abstract

The Crop and Fertilizer Recommendation System is a Python-based Machine Learning project aimed at recommending optimal crops to farmers based on various soil properties and environmental factors. The goal is to leverage data-driven insights to suggest the most suitable crops using the right fertilizer types, thereby enhancing agricultural productivity and promoting sustainable farming. In this project, we will develop a predictive model that can analyze soil nutrients (such as Nitrogen, Phosphorus, Potassium levels), climatic conditions (including temperature and humidity), and rainfall patterns, along with the type of fertilizer to recommend the most appropriate crop for cultivation. The goal is to predict the crop category and the appropriate fertilizer class, such as Wheat, Rice, Maize, etc., based on soil type. This aligns with the definition of a classification problem, where the target variable is categorical.