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Description

This PR adds a new Employee Attrition Prediction ML project to the repository. The project helps HR departments predict which employees are likely to leave the company, enabling proactive retention strategies.

Key Features:

  • Analyzes demographics (age, gender, education)
  • Evaluates job-related factors (department, role, tenure)
  • Considers compensation and work-life balance metrics
  • Uses multiple ML algorithms (Random Forest, Gradient Boosting, Neural Network)
  • Provides actionable insights for HR decision-making

Type of change

  • Added a new machine learning frameworks, libraries or software.
  • Documentation update

Checklist:

  • My code follows the style guidelines of this project
  • I have performed a self-review of my own code
  • I have commented my code, particularly in hard-to-understand areas
  • I have made corresponding changes to the documentation
  • My changes generate no new warnings

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Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

@Raghu0703
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@sanjay-kv Hi! I have completed this pull request adding an Employee Attrition Prediction ML project to the repository. This project helps HR departments predict employee turnover and includes comprehensive documentation with project structure, dataset description, model details, and key insights. I would be grateful if you could kindly review and accept this contribution. Thank you for your time! 🙏

@sanjay-kv sanjay-kv merged commit f2149df into recodehive:main Nov 26, 2025
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2 participants