Description

This Django-based web application predicts crop yield using machine learning. It leverages a linear regression model trained on synthetic data to forecast yields based on input features like nitrogen, phosphorus, potassium levels, temperature, humidity, pH, and rainfall. Users can input these parameters to get predictions along with information about appropriate fertilizers and related crop images. The project also includes user authentication, password reset functionality, and contact forms for user interaction.