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attrition-analysis

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Predicting employee attrition entails gathering historical data on employees, identifying key features, training machine learning models, and deploying them for real-time predictions to aid in retention strategies and organizational stability. Regular monitoring and updates ensure ongoing effectiveness.

  • Updated May 11, 2024
  • Jupyter Notebook

The goal of this project is to analyze employee retention data to uncover insights that can help improve retention strategies. By identifying key factors that influence employee attrition, we aim to provide actionable recommendations for enhancing employee satisfaction and retention rates.

  • Updated Jul 17, 2024
  • Jupyter Notebook

This GitHub repository hosts a comprehensive HR attrition analysis report, providing valuable insights into employee turnover trends within an organization. The report includes in-depth statistical analysis, data visualizations, and actionable recommendations to help HR professionals and business leaders make informed decisions to reduce attrition.

  • Updated Jan 27, 2024

IBM is an MNC and Attrition is a major risk to service-providing organizations where experienced people are the assets Here, I've created a program with Logistic Regression which would analyze an Organization Dataset and explore the attrition rate for various parameters and help in predicting the employees who are likely to leave.

  • Updated Aug 26, 2023
  • Jupyter Notebook

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