https://github.com/soupu07/ibm-employee-attrition-prediction

The aim of this project analyzes factors driving IBM employee attrition and predicts those likely to leave, helping the organization understand turnover causes and improve retention and performance.
https://github.com/soupu07/ibm-employee-attrition-prediction

data-science data-science-projects data-visualization machine-learning python python-data-analysis python-programming-language python-project

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The aim of this project analyzes factors driving IBM employee attrition and predicts those likely to leave, helping the organization understand turnover causes and improve retention and performance.

• Host: GitHub
• URL: https://github.com/soupu07/ibm-employee-attrition-prediction
• Owner: Soupu07
• Created: 2024-10-24T19:20:40.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-10-24T20:43:29.000Z (4 months ago)
• Last Synced: 2024-11-16T03:48:34.970Z (3 months ago)
• Topics: data-science, data-science-projects, data-visualization, machine-learning, python, python-data-analysis, python-programming-language, python-project
• Language: Jupyter Notebook
• Homepage:
• Size: 237 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# IBM-Employee-Attrition-Prediction

Employee attrition is described as the natural process through which employees leave their employment and are not quickly replaced, such as by resignation for personal reasons or retirement. Employee turnover is recognized as a critical issue for all businesses these days, owing to its negative impact on workplace productivity and meeting corporate goals on time. To maintain a competitive edge over its competitors, a business should make it a priority to reduce staff turnover. As a result, for the better growth of a corporation, it is critical for company leaders to understand the primary reasons why their employees choose to quit the firm, and then take appropriate actions to enhance their organization's efficiency, general workflow, and business performance.

**Context**

**Watson Analytics Sample Data**

Uncover the factors that lead to employee attrition and explore important questions such as ‘show me a breakdown of distance from home by job role and attrition’ or ‘compare average monthly income by education and attrition’.

**Content**

This the data about the employee on various factor influencing the attrition from the company. Predict the Attrition of an employee based on the various factor given

**About Dataset**

I) **Department**

    1.	Sales	

    

    2.	Research and Development

    

    3.	Human Resources

II) **Education Field**

     1.	Life Sciences

     

     2.	Medical

     

     3.	Marketing

     

     4.	Technical Degree

     

     5.	Human Resource

     

     6.	Other

III) **Marital Status**

      1.	Single

    

      2.	Married

    

      3.	Divorced

IV) **Job Satisfaction**

V) **Monthly Income**

VI) **Work Life Balance**

      

**Perform the Following Functions and Find out:**

a)	**Predict the Attrition of an employee based on the various factors mentioned above.**

b)	**Prepare a histogram of the Age Distribution of Employees.**

c)	**Prepare a plot presenting the Attrition Breakdown of Employees**

d)	**Perform Logistic Regression of the Data**

e)	**Perform metrics for the accuracy score and classification report**