Employee Attrition Prediction Using Machine Learning

提供方
Coursera Project Network
在此指導 項目中,您將:

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

Clock2 hours
Beginner初級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

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.

您要培養的技能

Machine Learning RegressionData ScienceArtificial Neural NetworkMachine Learningregression

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Understand the Problem Statement and Business Case

  2. Import Libraries and Datasets

  3. Perform Data Visualization

  4. Perform Data Visualization - Continued

  5. Create Training and Testing Datasets

  6. Understand the Intuition Behind Logistic Regression

  7. Train and Evaluate a Logistic Regression Model

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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