Exploratory data analysis project on Employee Attrition dataset. EMPLOYEE ATTRITION RATE : Employee Attrition Rate is calculated as the percentage of employees who left the company in a given period to the total average number of employees within that period.

In this project I did Complete EDA, and Build a ML model that can accurately predict whether an Employee will be leave a company or not based on different factors.

In this project, I built predictive models to predict employee attrition rate and how best this fictional company can use my “best" model to improve their employee retention rate. The techniques I used to build my “best” model are forward stepwise, Lasso, and classification.

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.

Address employee attrition effectively with this mini project. Discover a comprehensive solution leveraging data analytics and machine learning techniques. Uncover insights, build predictive models, and implement strategies to mitigate attrition risks, fostering a resilient and productive workforce.