This repository contains a machine learning project that utilizes a Linear Regression model to predict the probability of crop yield based on provided data. The project is built using the Flask Python framework, and the trained model is saved and loaded using the pickle library.
Crop yield prediction is a crucial aspect of agricultural planning and decision-making. This project aims to provide a simple and user-friendly solution for predicting crop yields based on historical data.
The Linear Regression model is trained using the provided dataset to establish relationships between various factors influencing crop yield, such as temperature, rainfall, and soil nutrients. The trained model is then integrated into a web application using Flask, allowing users to input specific data and obtain the predicted crop yield probability.