Welcome to this project-based course on Predicting Employee Turnover with Decision Trees and Random Forests using scikit-learn. In this project, you will use Python and scikit-learn to grow decision trees and random forests, and apply them to an important business problem. Additionally, you will learn to interpret decision trees and random forest models using feature importance plots. Leverage Jupyter widgets to build interactive controls, you can change the parameters of the models on the fly with graphical controls, and see the results in real time!
Predict Employee Turnover with scikit-learn
Predict Employee Turnover with scikit-learn
Instructor: Snehan Kekre
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Learn, practice, and apply job-ready skills with expert guidance
4.4
(254 reviews)
Intermediate level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
Apply decision trees and random forests with scikit-learn to classification problems
Interpret decision trees and random forest models using feature importances
Tune model hyperparamters to improve classification accuracy
Create interactive, GUI components in Jupyter notebooks using widgets
Skills you'll practice
Details to know
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Add to your LinkedIn profile
Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Importing Libraries
Exploratory Data Analysis
Encode Categorical Features
Visualize Class Imbalance
Create Training and Test Sets
Build a Decision Tree Classifier with Interactive Controls
Build a Decision Tree Classifier with Interactive Controls (Continued)
Build a Random Forest Classifier with Interactive Controls
Feature Importance and Evaluation Metrics
Recommended experience
Some experience in Python programming and machine learning theory is recommended.
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Instructor
Instructor ratings
4.6 (18 ratings)Offered by
How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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