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Let’s begin our coding quest! Below is the complete README.md file for the "Intelligent Crop Recommendation Portal" repository.

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Intelligent Crop Recommendation Portal 🌾

This repository hosts the Intelligent Crop Recommendation Portal, a machine learning-powered web application designed to assist farmers and agricultural specialists in selecting the best crops and fertilizers based on soil characteristics and environmental parameters. Developed by Aman Attar, this project leverages nutrient data and predictive models to make insightful agricultural recommendations.

For a detailed report on the project's development, please refer to the Medium Article.

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Table of Contents

• About the Project
• Features
• Directory Structure
• Installation
• Usage
• Contributing
• License

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About the Project

The Intelligent Crop Recommendation Portal is a web-based recommendation system aimed at improving crop yield and fertilizer application by utilizing machine learning models. By analyzing soil nutrient levels and environmental factors, the portal provides recommendations on the most suitable crops, as well as optimal fertilizers and pesticides, fostering sustainable agricultural practices.

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Features

• Crop Recommendation: Suggests the best crops based on soil nutrient content and environmental data.
• Fertilizer Recommendation: Provides fertilizer suggestions tailored to crop types and soil characteristics.
• Pesticide Guidance: Recommends pesticides for managing common pests.
• Data Visualization: Offers visual insights on soil nutrients and crop recommendations.
• User-Friendly Web Application: Interactive interface for easy access to recommendations and information.

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Directory Structure

Data Directory

• Crop_NPK.csv and crop_recommendation.csv: Contain nutrient values and recommendations for different crops.

Models

• cnn_model.ipynb and crop_model.ipynb: Jupyter notebooks for training and evaluating models.
• Trained_Model_1.h5: Saved model file used for crop and fertilizer recommendations.

Application Files

• app.py: Main application file, likely a Flask app for running the web server.
• requirements.txt and runtime.txt: Specify Python dependencies and runtime requirements.

Frontend

• Static: Contains CSS, JavaScript, and image resources for the web application's front end.
• Templates: HTML templates such as CropRecommendation.html and FertilizerRecommendation.html for rendering the crop and fertilizer recommendation views.

Utils Directory

• fertilizer.py: Contains utility functions for suggesting fertilizers based on crop nutrient requirements.

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Installation

Follow these steps to set up and run the application locally.

1. Clone the Repository:

   git clone https://github.com/amanattar/crop
   cd crop

2. Install Dependencies:
   Ensure Python is installed, then run:

   pip install -r requirements.txt

3. Run the Application:

   python app.py

   The app will start on localhost:5000 by default.

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Usage

1. Crop Recommendation:

   • Navigate to the Crop Recommendation page.
   • Input soil parameters (NPK values, moisture, temperature, etc.).
   • Receive a list of recommended crops based on the provided data.

2. Fertilizer Advice:

   • Use the Fertilizer Recommendation section.
   • Input the crop type and soil nutrient needs to get tailored fertilizer suggestions.

3. Pesticide Information:

   • Access information on pest management strategies.
   • Find suitable pesticides for common pests based on crop types and region.

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Contributing

Contributions are highly encouraged! To get started:

1. Fork the Repository and clone it locally.

2. Create a New Branch for your feature or bug fix:

   git checkout -b feature/YourFeatureName

3. Commit Changes and push to your branch:

   git push origin feature/YourFeatureName

4. Submit a Pull Request for review.

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License

This project is licensed under the MIT License. See the LICENSE file for more details.

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With the Intelligent Crop Recommendation Portal, you can easily determine the optimal crops and fertilizers tailored to specific soil and environmental conditions. Whether you are a developer, farmer, or agricultural scientist, we welcome your contributions and feedback to improve the system.

Enjoy farming smarter! 🌱✨

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