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The Brief
Arizona Engineering Services, a subsidiary of the Arizona Group of Companies, is struggling with employee retention. The rate of employee attrition is rising annually, and the cost of onboarding new employees is increasing.
Management needs insights into the employees who are leaving. This will help them identify the reasons for employee departures and develop employee-friendly policies and work environments to prevent further attrition.
The Human Resources Manager would like you to;
- Explore the HR Attrition data and create a machine-learning model to predict employee attrition.
- Get the most important features needed that could be deployed to production shortly.
Tools: Scikit Learn, Pandas, Numpy, Flask, HTML, CSS
Process and Implementation
Data Exploration
Work Flow
Development
Data Exploration
Data Exploration
Data Dictionary: Table & Columns Definition (not included in the demo).
Data: HR_Attrition.xlsx
Work Flow
The Work Flow
- Data Exploration (EDA)
- Data Cleaning, Transformation and Feature Selection
- Model Comparison
- Pipeline Creation (transformer, preprocessor, model training and tuning)
- Model Evaluation
- Feature Importance
Development
