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.
Employee Attrition Prediction Using Machine Learning
Gain insight into a topic and learn the fundamentals.
4.4
(13 reviews)
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Understand the theory and intuition behind logistic regression classifier models
Build, train and test a logistic regression classifier model in Scikit-Learn
Perform data cleaning, feature engineering and visualization
Details to know
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Assessments
1 assignment
Taught in English
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There is 1 module in this course
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.
What's included
1 reading1 assignment1 ungraded lab1 plugin
Instructor
Offered by
Explore more from Machine Learning
University of Washington
S.P. Jain Institute of Management and Research
Johns Hopkins University
Wesleyan University
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4.4
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5
Reviewed on Nov 17, 2022
Great explanation of step wise process to go from EDA to Train/test/split to building a model.
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
More questions
Financial aid available,