Ansu-John / IBM-HR-Analytics-Employee-Attrition

Predict employee attrition using LogisticRegression and RandomForestClassifier.

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Employee Attrition Analysis

OBJECTIVE

Employee attrition is the rate at which employees leave a company. The goal of this analysis is to model employee attrition and determine the most dominant contributing factors that govern this turnover. Through this kind of analysis, we can understand how many employees are likely to leave, while also determining which employees are at the highest risk and for what reasons.

Data Visulization for the same in Tableau can be seen in the link

DATASET USED

The dataset used in this analysis is provided from IBM HR to study about employee attrition, which can be found here.

TOOLS

Python - Data modelling using LogisticRegression and RandomForestClassifier, Data preprocessing using LabelEncoder and OneHotEncoder

TECHNIQUES

As I have already used Tableau to analyse the data, I have only build data models to predict the employee attrition in this case study.

About

Predict employee attrition using LogisticRegression and RandomForestClassifier.

License:MIT License


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Language:Jupyter Notebook 100.0%