The Crop and Fertilizer Recommendation System is a Python Machine Learning project aimed at recommending optimal crops to farmers based on various soil and environmental factors. The goal is to leverage data-driven insights to suggest the most suitable crops using different fertilizers, thereby enhancing agricultural productivity and sustainability. In this project, we will develop a model that can analyze soil characteristics (like Nitrogen, Phosphorus, Potassium levels), environmental conditions (temperature, humidity), and rainfall patterns and type of fertilizer to recommend the most suitable crops for cultivation. The goal is to predict the type of crop to be recommended, and the type of fertilizer which falls into distinct categories or classes. For instance, the output might include classes such as Wheat, Rice, Maize, etc. along with details for fertilizer required based on the soil type.This aligns with the definition of a classification problem where the target variable is categorical.
