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Employee Churn Prediction System

Overview

This project aims to predict employee churn using machine learning techniques, specifically deep learning with Keras and TensorFlow. The system is designed with a user-friendly interface using HTML and JavaScript for the frontend, and it employs Spring Boot for the Java backend and Flask for the Python-based machine learning model.

Table of Contents

Features

  • Predicts whether an employee will churn based on various input features.
  • User-friendly web interface for data input.
  • Real-time prediction results displayed on the frontend.
  • Integrated API using Flask and Spring Boot for seamless communication.

Technologies Used

  • Frontend:

    • HTML
    • JavaScript

  • Backend:

    • Spring Boot (Java)
    • Flask (Python)

  • Machine Learning:

    • Keras
    • TensorFlow
    • pyhton
    • flask

Installation & Guide

To set up the project locally, follow these steps:

  1. Clone the repository:

    git clone https://github.com/yourusername/employee-churn-prediction.git
cd employee-churn-prediction

  2. Start the Spring Boot Server(after going to specific diretory):

    ./mvnw spring-boot:run

  3. Start the Flask Server(after going to specific diretory):

    python app.py

  4. Download the LiveServer Extenstion in your IDE then go to diretory Frontend run index.html with live server