Prediction of Cumulative Grade Point Average 😎

👋 About Project

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In this project, we will experiment with a real world dataset of grades with CGPA, and to explore how machine learning algorithms can be used to find the patterns in data.

We have a dataset of 42 features of different courses. In corresponding to these we are required to predict CGPA. We can solve this problem using SUPERVISED LEARNING algorithms.

🌳 Structure

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├── 📁 Deployment_Folder
│   ├── 📁 statics
│   │   ├── 📄 main.css
│   │
│   ├── 📁 templates
│   │   ├── 📄 index.html
│   │   ├── 📄 model_1.html
│   │   ├── 📄 model_2.html
│   │   └── 📄 model_3.html
│   │
│   ├── 📄 Dockerfile
│   │
│   ├── 📄 Procfile
│   │
│   ├── 📄 app.py
│   │
│   ├── 🖼️ GradientBoostingRegressor.pkl
│   ├── 🖼️ linear_regression.pkl
│   ├── 🖼️ RandomForestRegressor.pkl
│   └── 📄 requirements.txt
│   │
├── 🗨️ The_Grades_Dataset.csv
│   │
├── 💣 main_notebook.ipynb
│   │
├── 📄 LICENCS
│   │
└── 📄 README.md

🔮 User Interface

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• The UI of the project is built using Flask. HTML and CSS.
• https://cgpa-prediction-3.herokuapp.com/

🏡 Developer Setup Guide

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⏮️ Prerequisites

• Account on Heroku
• Heroku CLI
• Docker
• Docker Desktop

Move in a woking directory

`cd Deployment_Folder`

Create Virtual Enviroment

`python venv -m my-venv`

Activate Virtual Enviroment

`.\my-venv\Scipts\activate`

Install all Requirements

`pip install requirements.txt`

Run Flask app locally:

 `python app.py'

Build the docker image

  `docker build -t docker_application_name . '

Run the docker container and test it locally

   `docker images'
   `docker run --name flask1 -dit -p 5000:5000 docker_application_name'
   `docker ps'

Login to heroku container registry

   `heroku container:login'

Create an heroku app

   `heroku create heroku_app_name'

Build the image and push the image to heroku registry.

   `heroku container:push web -a heroku_app_name'

Creating the container on heroku host and hosting it publicly

   `heroku container:release web -a heroku_app_name'

To open the app in your default browser

   `heroku open -a heroku_app_name'

⚒️ Built Upon

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- Python
- Heroku
- Docker

🔧 Tools Used

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- Visual Studio Code
- Google Colaboratory
- Microsoft Excel

🧐 Medium Blog

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If you want to learn more about Data Science and Machine Learning of this project. You can read this Blog.

📋 License

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This project is licensed under the MIT License - see the LICENSE file for details.