https://github.com/mugilan1309/farmiq
🌱 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.
https://github.com/mugilan1309/farmiq
agriculture crop-recommendation fertilizer-recommendation machine-learning python sqlite streamlit
Last synced: about 2 months ago
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🌱 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.
- Host: GitHub
- URL: https://github.com/mugilan1309/farmiq
- Owner: Mugilan1309
- Created: 2025-02-05T14:19:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-09T14:25:43.000Z (over 1 year ago)
- Last Synced: 2025-03-17T05:34:49.793Z (over 1 year ago)
- Topics: agriculture, crop-recommendation, fertilizer-recommendation, machine-learning, python, sqlite, streamlit
- Language: Python
- Homepage: https://farmiq.streamlit.app/
- Size: 618 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 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](https://farmiq.streamlit.app/)
## 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
```bash
# 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