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This is Class Machine learning. I design Web Applications in Designer .html use .py and then train the model to use. Then insert it into the program

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Python Web Application with Ensemble Techniques

This project is a machine learning web application that uses Ensemble Techniques to train multiple models and select the best ones for prediction. The application is developed using Flask, and the trained model is deployed on Render.

🚀 Live Demo

Click here to access the deployed application


📌 Project Overview

The goal of this project is to predict employee status (Still Employed or Resigned) based on various factors, such as:

  • Age
  • Length of Service
  • Salary
  • Gender
  • Marital Status

To achieve high prediction accuracy, the project employs Ensemble Learning techniques, specifically:

  • Voting Classifier (Hard Voting)
  • Stacking Classifier with a meta-model (Random Forest)

The best-performing models are selected based on accuracy and then used in the ensemble model.


⚙️ Technologies Used

  • Python (Machine Learning Model Training)
  • Flask (Backend Web Framework)
  • Scikit-learn (ML Models & Preprocessing)
  • Pandas (Data Handling)
  • Joblib (Model Persistence)
  • HTML & Bootstrap (Frontend UI)
  • Render (Cloud Deployment)

📂 Project Structure

📁 project-root/
│── 📁 model/                # Contains trained models
│   │── Train_model.py       # Train multiple models and save the best one
│   │── Load_Train_Best_Model.py  # Load and use the best model
│   │── Test_Model.py        # Test the trained model
│── 📁 templates/            # HTML templates for Flask
│── 📁 static/               # CSS & assets
│── app.py                   # Main Flask application
│── data.csv                 # Dataset used for training
│── requirements.txt         # Dependencies
│── README.md                # Project documentation

🛠️ How to Run the Project Locally

1️⃣ Clone the repository

git clone https://github.com/your-repo-url.git
cd project-root

2️⃣ Install dependencies

pip install -r requirements.txt

3️⃣ Train the model

Run the script to train models and save the best one:

python model/Train_model.py

4️⃣ Run the Flask app

python app.py

The application will be available at http://127.0.0.1:5000/


🔥 Future Improvements

  • Improve model performance using feature engineering
  • Implement more advanced ensemble techniques
  • Enhance UI design for better user experience
  • Deploy on additional cloud platforms

📞 Contact

Author: pathipat.mattra@gmail.com & pathipat.m@kkumail.com

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This is Class Machine learning. I design Web Applications in Designer .html use .py and then train the model to use. Then insert it into the program

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