Employee Attrition Prediction Using Machine Learning
In this project-based course, we will build, train and test a machine learning model to predict employee attrition using features such as employee job satisfaction, distance from work, compensation and performance. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Extreme Gradient Boosted Trees (XG-Boost). This project could be effectively applied in any Human Resources department to predict which employees are more likely to quit based on their features.
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- Level Beginner
- Duration 3 hours
- Course by Coursera Project Network
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In this project-based course, we will build, train and test a machine learning model to predict employee attrition using features such as employee job satisfaction, distance from work, compensation and performance. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Extreme Gradient Boosted Trees (XG-Boost). This project could be effectively applied in any Human Resources department to predict which employees are more likely to quit based on their features. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.Modules
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- Employee Attrition Prediction Using Machine Learning
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- Project Overview
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Discover the "Employee Attrition Prediction Using Machine Learning" course, designed for beginners in Data Science & AI. Led by Coursera, you'll learn to build, train, and test models using logistic regression and XG-Boost to predict employee attrition based on job satisfaction, distance, compensation, and performance. Perfect for HR professionals, this 180-minute course is available for free, with an optimal experience for North American learners.
Ryan Ahmed