A.G
Abhinay Goswami

Crop Yield Prediction

The Crop Yield Prediction project uses machine learning to predict agricultural yields based on various parameters like weather, soil, and crop type. Built with Python, it leverages libraries such as Pandas, Scikit-learn, and TensorFlow.

Project Image

Project Overview

Welcome to the Crop Yield Prediction repository! This project aims to leverage machine learning techniques to predict crop yields, providing valuable insights for farmers, agronomists, and policymakers. By analyzing various factors such as weather conditions, soil properties, and agricultural practices, this tool helps in making informed decisions to enhance agricultural productivity and sustainability.

Utilizes advanced machine learning algorithms to predict crop yields accurately.Incorporates comprehensive data analysis to understand the impact of different factors on crop yield. Offers an intuitive interface for users to input data and view predictions. Includes graphical representations of data and predictions to facilitate easy interpretation. Designed to handle large datasets and adaptable to various crops and regions.

Tools Used

Python
Pandas
Numpy
Matplotlib
Seaborn
Regression
Decision Tree
GIT
GITHUB