AdmitAssist is a Django-based web application designed to help students assess their chances of gaining admission to their desired Master’s programs. By entering their academic details, users can receive a percentage likelihood of acceptance based on various machine learning and deep learning models.
- Predictive Admission Analysis: Users can input their academic details and receive a percentage chance of admission.
- Multiple Model Evaluations: The app uses various machine learning (ML) and deep learning (DL) models, such as Random Forest, SVM, Logistic Regression, and ANN, to predict outcomes.
- User-Friendly Interface: The frontend is designed for ease of use, allowing students to interact with the application seamlessly.
- Backend: Python, Django
- Frontend: HTML, CSS, JavaScript
- Machine Learning: Random Forest, SVM, Logistic Regression, Artificial Neural Networks (ANN)
- Database: MySQL
Ensure you have the following installed:
- Python 3.x
- pip (Python Package Installer)
- MySQL
git clone https://github.com/Shivam093/Admit-Assist.gitInstall the necessary dependencies using the requirements.txt file.
pip install -r requirements.txtStart the Django development server:
python manage.py runserver- Enter Academic Details: Fill out the form with your GPA, test scores, and other academic information.
- Select Desired University: Choose from a list of universities to see your admission chances.
- View Prediction: Receive a percentage chance of admission based on the chosen model.
- University Recommendations: Suggest alternative universities based on user input and model predictions.
- Hybrid Modeling: Combine multiple models to improve prediction accuracy.
- Expanded Dataset: Incorporate more data points from various universities to improve model training.
Contributions are welcome! Feel free to open an issue or submit a pull request.