ujjwal4maletha/fertilizer-prediction repository overview

Fertilizer Recommendation Model Overview Welcome to the Fertilizer Recommendation Model repository! This repository hosts a Dockerized Flask application that provides fertilizer recommendations based on various soil and crop parameters. The model, trained on extensive agricultural data, predicts the most suitable fertilizer to optimize crop yield.

Features Machine Learning Model: Utilizes a pre-trained model (Fertilizer_Recommendation_model_2.pkl) to provide accurate fertilizer recommendations.

REST API: Exposes endpoints for easy integration with other applications, including a /predict endpoint for making predictions.

Lightweight Image: Built using an optimized python:3.9-slim base image to ensure a small footprint and fast deployment.

Multi-Stage Build: Employs multi-stage builds to keep the final image lean by including only necessary dependencies.

How to Use

1. Pull the Docker Image: docker pull ujjwal4maletha/fertilizer-prediction:latest

2. Run the Container: docker run -p 5000:5000 ujjwal4maletha/fertilizer-prediction:latest

3. Access the API: The API will be accessible at http://localhost:5000/predict⁠.

   Example request:

{ "Temperature": 25, "Humidity": 50, "Moisture": 20, "Nitrogen": 10, "Potassium": 5, "Phosphorous": 3, "Soil Type": "Sandy", "Crop Type": "Wheat" }

Contributing

Feel free to fork the repository and submit pull requests. Contributions are welcome!

License

This project is licensed under the MIT License.

Contact

For questions or support, please open an issue or contact [email protected]⁠.