Employee Attrition Prediction Using Machine Learning

提供方
Coursera Project Network
在此指导项目中,您将:

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初级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

  • Machine Learning Regression
  • Data Science
  • Artificial Neural Network
  • Machine Learning
  • regression

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  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

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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常见问题

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