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Rbholika/EduPredict

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EduPredict: Machine Learning Insights for Academic Performance

Home UI EduPredict UI

Project Overview

EduPredict is a machine learning application designed to provide insights into academic performance. With an 90% success rate, this application leverages Python-based scripts to train, deploy, and evaluate machine learning models locally.

Key Achievements

  • Developed and deployed a machine learning application with an 90% success rate.
  • Streamlined local execution using Python commands and pre-configured scripts.
  • Optimized performance through efficient code and dependency management.

Getting Started

Prerequisites

  • Python 3.8 or higher
  • Pip (Python package installer)

Setup

  1. Clone the repository:

    git clone https://github.com/your-username/your-repo.git
    cd your-repo
  2. Create and activate a virtual environment:

    python -m venv venv
    source venv/bin/activate # On Windows use `venv\Scripts\activate`
  3. Install dependencies:

    pip install -r requirements.txt

Running the Application

  1. Train the model:

    python train.py
  2. Run the application:

    python application.py

Usage

  • Training Script: train.py trains the machine learning model and saves it to disk.
  • Application Script: application.py runs the application and serves predictions.

Troubleshooting

  • Dependency Issues:

    • Ensure all packages are installed correctly using pip install -r requirements.txt.
    • Check for any missing or outdated packages.
  • Execution Errors:

    • Verify Python version compatibility.
    • Check logs for detailed error messages.

Contributing

Feel free to submit issues, pull requests, or suggestions. Please follow the project's code of conduct and contribution guidelines.

About

Unlock academic insights with EduPredict, a Python-based machine learning tool achieving up to 90% accuracy. Train, evaluate, and deploy models locally with ease. Built for educators, students, and researchers aiming to forecast academic success.

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