https://github.com/sahilll94/crop-recommendation-system

A Crop Recommendation System using machine learning to predict the best crop based on soil and environmental conditions.
https://github.com/sahilll94/crop-recommendation-system

machine-learning streamlit webapp

Last synced: about 2 months ago
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A Crop Recommendation System using machine learning to predict the best crop based on soil and environmental conditions.

• Host: GitHub
• URL: https://github.com/sahilll94/crop-recommendation-system
• Owner: Sahilll94
• Created: 2025-03-04T16:50:05.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-03-04T17:17:18.000Z (over 1 year ago)
• Last Synced: 2025-03-04T17:40:50.662Z (over 1 year ago)
• Topics: machine-learning, streamlit, webapp
• Language: Jupyter Notebook
• Homepage: https://crop-recommendation-system-sahil.streamlit.app/
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 🌾 Crop Recommendation System  

## 📌 Overview  

This is a machine learning-based **Crop Recommendation System** that suggests the best crop to grow based on soil nutrients (N, P, K), temperature, humidity, pH, and rainfall.  

## 🚀 Features  

- Predicts the most suitable crop using ML algorithms.  

- User-friendly web interface built with **Streamlit**.  

- Accepts soil and weather inputs to make recommendations.  

## 📊 Dataset  

The model is trained on an agricultural dataset containing information about:  

- **Soil Nutrients:** Nitrogen (N), Phosphorus (P), Potassium (K)  

- **Environmental Factors:** Temperature (°C), Humidity (%), Rainfall (mm), pH  

## 🛠 Tech Stack  

- **Frontend:** Streamlit  

- **Backend:** Python (Flask/FastAPI for API)  

- **ML Model:** Random Forest / Decision Tree