Kabr Prediction

This model is designed to determine the age of a crab based on its other physical characteristics. Using this model, it is possible to determine the age of a crab through its other data. This project demonstrates the use of various machine learning algorithms and data processing techniques to achieve accurate predictions.

Table of Contents

• Installation
• Usage
• Project Structure
• Libraries Used
• License
• Contributing
• Contact

Installation

1. Clone the repository:

   git clone https://github.com/UznetDev/Kabr-prediction.git
   

2. Navigate to the project directory:

   cd Kabr-prediction
   

3. Create a virtual environment:

   python -m venv env
   

4. Activate the virtual environment:
   • On Windows:

     env\Scripts\activate
     

   • On macOS and Linux:

     source env/bin/activate
     

5. Install the necessary libraries:

   pip install -r requirements.txt
   

Usage

To explore and run the project:

1. Open the model.ipynb file in Jupyter Notebook or JupyterLab.
2. Follow the instructions within the notebook to understand the data processing steps, model training, and evaluation.

Project Structure

• README.md: Provides an overview of the project, installation instructions, and usage guidelines.
• model.ipynb: Jupyter Notebook containing the machine learning workflow.
• test_model.ipynb: Jupyter Notebook for testing model.
• requirements.txt: A list of required dependencies.
• .gitignore: Specifies files and directories to be ignored by git.

Libraries Used

• Pandas: Data manipulation and analysis.
• NumPy: Numerical operations and array handling.
• Scikit-learn: Machine learning model building and evaluation.
• Warnings: Handling and filtering warning messages.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any changes.

1. Fork the Repository: Click on the Fork button at the top right corner of this page to create a copy of this repository under your GitHub account.

2. Clone the Forked Repository:

   git clone https://github.com/UznetDev/Kabr-prediction.git
   cd Global-Statistics-Dashboard
   

3. Create a New Branch:

   git checkout -b feature/YourFeatureName
   

4. Commit Your Changes:

   git add .
   git commit -m 'Add some feature'
   

5. Push to the Branch:

   git push origin feature/YourFeatureName
   

6. Create a Pull Request: Open a pull request to the original repository.

Contact

If you have any questions or suggestions, please contact:

• Email: [email protected]
• GitHub Issues: Issues section
• GitHub Profile: UznetDev
• Telegram: UZNet_Dev
• Linkedin: Abdurahmon Niyozaliev

Thank you for your interest in the project!