Develop a Machine Learning model that can able to predict which employesses are more likely to quit

Motivation

Research shows , small companies spend 40% working hours that don't generate any income hiring is one of them.Hiring costed on average 7645 US Dollar. This Data was collect by HR team for analyze and buid model which employees prone to quit.Identify them earlier and take necessary measures to stop quitting is great advantageous for HR team.

Overview

This is a classification model. Where used Logistic Regression and Ensemble model(Random Forest),on top to Scikitlearn. Also trained on Deep Learning model,trained on the top of Keras API, to observe which model works well.

Instalation

The Code is written in Python 3.8.5 .

Exploratory Data Visualizatio

Explore the whole dataset

Corelations

Technologies Used