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πŸš—πŸ’₯ Accident damage estimation for insurance companies using the CatBoost algorithm. πŸ“ŠπŸ“ˆ This advanced technique utilizes machine learning to provide accurate estimates for assessing damages caused by accidents. πŸ’―πŸ’Ό Enhance efficiency and accuracy in insurance claim processes with the power of CatBoost! πŸ€–πŸ“‰

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MohammadMoradpoor/InsuranceAccidentEstimate

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InsuranceAccidentEstimate

InsuranceAccidentEstimate is a repository that contains a Python notebook named CatBoostInsuranceRegression.ipynb. This notebook solves the problem of estimating accident damages for an insurance company using the CatBoost algorithm.

Introduction

Accurate estimation of accident damages is crucial for insurance companies to assess claims and determine appropriate coverage. The CatBoostInsuranceRegression.ipynb notebook provides a solution to this problem by leveraging the CatBoost algorithm, which is a gradient boosting framework.

Installation & Usage

To use the CatBoostInsuranceRegression.ipynb notebook, follow these steps:

  1. Clone the repository to your local machine:

    git clone https://github.com/MohamadsalehMoradpoor/InsuranceAccidentEstimate.git
  2. Install the required dependencies:

    pip install -r requirements.txt
  3. Launch Jupyter Notebook:

    jupyter notebook
  4. In the Jupyter Notebook interface, open the CatBoostInsuranceRegression.ipynb notebook.

  5. Follow the instructions provided in the notebook to execute the code cells and run the CatBoost regression model for accident damage estimation.

Note: Make sure you have the required dataset or data files available in the appropriate location. The notebook may expect specific data files or data preprocessing steps. Adjust the code accordingly to fit your dataset and requirements.

Contributing

If you'd like to contribute to this repository, you can follow these steps:

  1. Fork the repository on GitHub.
  2. Clone the forked repository to your local machine.
  3. Create a new branch and make your modifications.
  4. Commit and push your changes to your forked repository.
  5. Submit a pull request, describing your changes and the motivation behind them.

Contact

If you have any questions or suggestions regarding this repository, please feel free to contact the repository owner.

Thank you for using the InsuranceAccidentEstimate repository! We hope it proves to be useful for your insurance estimation needs.

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πŸš—πŸ’₯ Accident damage estimation for insurance companies using the CatBoost algorithm. πŸ“ŠπŸ“ˆ This advanced technique utilizes machine learning to provide accurate estimates for assessing damages caused by accidents. πŸ’―πŸ’Ό Enhance efficiency and accuracy in insurance claim processes with the power of CatBoost! πŸ€–πŸ“‰

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