A Machine Learning-based web application that predicts student eligibility for placements and recruitment opportunities based on academic performance, technical skills, certifications, projects, internships, and company-specific criteria.
The system automates the candidate screening process by analyzing student profiles and generating eligibility results along with ranking scores, helping institutions and recruiters make faster and more accurate decisions.
- Student Eligibility Prediction using Machine Learning
- Academic & Skill-Based Candidate Filtering
- Company Criteria Matching
- Candidate Ranking System
- Real-Time Eligibility Evaluation
- Interactive Streamlit Dashboard
- Student Data Upload (CSV/Excel)
- Downloadable Shortlisted Candidate Reports
- Analytics and Performance Insights
- Streamlit
- Python
- Scikit-Learn
- Pandas
- NumPy
- PostgreSQL
- Matplotlib
- Plotly
student-eligibility-prediction-using-machine-learning/
│
├── dataset/
├── model/
├── database/
├── screenshots/
├── app.py
├── requirements.txt
└── README.md
git clone https://github.com/Owskar/student-eligibility-prediction-using-machine-learning.git
cd student-eligibility-prediction-using-machine-learningpip install -r requirements.txtstreamlit run app.pyThe system evaluates students using:
- CGPA
- Technical Skills
- Certifications
- Projects
- Internship Experience
- Attendance
- Backlog Status
- Company Requirements
The application provides:
- Eligibility Status (Eligible / Not Eligible)
- Match Score
- Candidate Ranking
- Shortlisted Student List
- Analytics Dashboard
- Upload student data.
- Define company eligibility criteria.
- Preprocess and analyze the dataset.
- Apply Machine Learning-based evaluation.
- Generate eligibility results and ranking scores.
- Display results through the Streamlit dashboard.
- Export shortlisted candidates.
- Resume Parsing using NLP
- AI-Based Skill Gap Analysis
- Company Recommendation System
- Email Notifications
- Multi-College Integration
- Cloud Deployment
- AI Chatbot for Placement Assistance
- Campus Placement Management
- Student Employability Analysis
- Recruitment Screening
- Candidate Ranking and Shortlisting
- Academic Performance Evaluation
Contributions are welcome.
- Fork the repository
- Create a feature branch
- Commit your changes
- Push the branch
- Open a Pull Request
This project is licensed under the MIT License.
Owskar Ganbawale
- Python Developer
- Machine Learning Enthusiast
- Full Stack Developer
If you found this project useful, please consider giving it a ⭐ on GitHub.