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A Polynomial Regression Model which works on JEE ADV Dataset to get a prediction model

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Mark2Rank JEE

Mark2Rank JEE is a simple tool designed to predict the rank of students based solely on their marks in the JEE Advanced examination. It provides a straightforward method to estimate your rank without leveraging historical data or machine learning models, relying purely on user input and a predefined mark-to-rank mapping.

Features

  • Rank Prediction: Quickly estimate your JEE Advanced rank by inputting your marks.
  • User-Friendly Interface: Simple and easy-to-use for students and educators.
  • Lightweight: No external datasets or complex models required, making it fast and efficient.

Getting Started

Follow these instructions to run the project locally.

Prerequisites

  • Python 3.x

Installation

  1. Clone the repository:
git clone https://github.com/5iri/Mark2Rank_JEE
  1. Navigate to the project directory:
cd Mark2Rank_JEE
  1. To run the program, you would need jupyter notebook.

Usage

  1. Run the rank_predictor.py script.
  2. Enter your JEE Advanced marks when prompted.
  3. The program will output an estimated rank based on the predefined mapping.

Contributing

Contributions to improve the tool or expand its functionality are welcome! Feel free to open an issue or submit a pull request.

Steps to Contribute:

  1. Fork the repository.
  2. Create a new branch: git checkout -b feature-branch
  3. Make your changes and commit them: git commit -m 'Add feature'
  4. Push the changes to your branch: git push origin feature-branch
  5. Open a pull request.

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A Polynomial Regression Model which works on JEE ADV Dataset to get a prediction model

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