Crops Recommender

A crops recommendation system using the Crop Recommendation Kaggle dataset.

Introduction

In agriculture, the precise recommendation of crops is pivotal in ensuring optimal yield and sustainability. As farmers and agricultural experts delve deeper into data-driven approaches, the significance of leveraging comprehensive datasets, particularly those about soil composition, becomes increasingly evident.

Features

• Data cleaning and exploratory analysis in Jupyter Notebook
• Feature based recommendation systems, using soil data such as Temperature, Ph levels, Humidity, NPK levels....
• User-friendly web interface

Screenshots

Home Page

Recommendation Result

Files

• Crop Recommendations.ipynb: Jupyter Notebook outlining data cleaning, analysis, and development of recommendation systems.
• app.py: Flask web application.
• templates/: HTML templates for the web interface.
• data/: original data, and indices used in app.py.
• figs/: Screenshots and images used in the README and documentation.
• static/: CSS styles.

Getting Started

1. Clone the repository:

   git clone https://github.com/yourusername/BookRecommender.git
   cd BookRecommender

2. Install dependencies:

   pip install -r requirements.txt

3. Run the Flask app:

   python app.py

4. Open your browser and go to http://localhost:5000/home

License

This project is licensed under the MIT License.