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FarmIQ - Crop & Fertilizer Recommendation System

FarmIQ is a machine learning-powered web application designed to provide smart crop and fertilizer recommendations based on soil and environmental parameters that are inputted manually. This serves as a simple demonstration of prediction and recommendation systems.

🚀 Live Demo: FarmIQ on Streamlit

Features

✅ Crop Recommendation – Suggests the best crops based on soil and climate data.
✅ Fertilizer Recommendation – Provides optimal fertilizer recommendations for better yield.
✅ Streamlit Frontend – A simple, interactive UI for users to input data and receive predictions.
✅ SQLite Database – Stores historical data for insights and analysis.
✅ Machine Learning Models – Uses trained models for accurate recommendations.

Tech Stack

  • Frontend: Streamlit
  • Backend: Python
  • Database: SQLite
  • Machine Learning: Scikit-learn
  • Version Control: GitHub

Installation & Setup

# Clone the repository
git clone https://github.com/Mugilan1309/FarmIQ.git
cd FarmIQ

# Install dependencies
pip install -r requirements.txt

# Run the Streamlit app (Ensure all files are in the same directory)
streamlit run app.py

© 2025 Mugilan1309 | FarmIQ

About

🌱 A simple machine-learning-based web app that provides crop and fertilizer recommendations based on manually entered soil and climate data. Built with Python, Streamlit, and SQLite.

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