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This project harnesses the capabilities of AI and ML to predict whether an employee is likely to leave the company or not using several Machine Learning algorithms.

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Bratajit-03/Attrition-Navigator

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Attrition Navigator

Attrition Navigator is a machine learning project that predicts employee attrition using various algorithms such as Logistic Regression, Naive Bayes, Decision Tree, Random Forest, and Gradient Boost. The project has achieved an accuracy of 89.11%.

Dataset

The dataset used in this project is available here. Please make sure to review and comply with the dataset's licensing and usage terms.

License

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

Dependencies

Make sure you have the following dependencies installed before running the project:

  • Python (>=3.6)
  • scikit-learn
  • pandas
  • numpy
  • seaborn
  • matplotlib

You can install these dependencies using the following command:

pip install scikit-learn pandas numpy seaborn matplotlib

How to Run

  1. Clone the repository:
git clone https://github.com/your-username/attrition-navigator.git
  1. Navigate to the project directory:
cd attrition-navigator
  1. Run the application:
python app.py

Visit http://localhost:5000 in your web browser to use the Attrition Navigator.

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This project harnesses the capabilities of AI and ML to predict whether an employee is likely to leave the company or not using several Machine Learning algorithms.

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