An intelligent AI/ML-powered web application that predicts campus placement probability for students based on their academic history, specialization, and work experience. The system provides data-driven insights to help students understand their placement chances and areas for improvement.
Currently runs on localhost - Perfect for academic demonstration and evaluation.
- Frontend: React.js + Vite
- Styling: Tailwind CSS + Framer Motion
- Backend: Flask (Python)
- ML Model: Support Vector Machine (SVM)
- Deployment: Ready for Vercel deployment
- ✅ Student placement probability prediction
- ✅ Academic performance analysis dashboard
- ✅ Personalized placement recommendations
- ✅ Interactive form with real-time validation
- ✅ Beautiful UI with animations
- ✅ Responsive design for all devices
- ✅ Data-driven insights from 215+ student records
Course: Artificial Intelligence and Data Science
Project Type: Mini Project
Academic Year: 2025
- Node.js (v16 or higher)
- Python 3.8+
- npm or yarn
- Clone the repository
git clone https://github.com/javking-pranesh/placement-predictor.git cd placement-predictor
📁 Project Structure
placement-predictor/ ├── src/ # React frontend │ ├── components/ # React components │ ├── services/ # API services │ └── ... ├── backend/ # Flask backend │ ├── app.py # Flask application │ ├── model/ # SVM model files │ └── requirements.txt └── README.md
🎯 Usage Fill in student academic details in the form
Click "Get Placement Prediction"
View probability score and personalized recommendations
Analyze key factors affecting placement chances
Use insights to improve academic performance
📈 Model Insights (Based on 215 records) Overall Placement Rate: 72.6%
Work Experience Impact: +36.3% placement chance
MBA Percentage > 65%: 85.2% placement rate
Mkt&Fin Specialization: +6.6% better placement
Degree Percentage > 70%: +27% advantage
SVM Model Accuracy: [88.37%]