Academic Success Prediction Application

Project Progress Report

Current Implementation Status

Core Features Implemented

1. Student Data Input System

   • GPA input (0.0 - 4.0 scale)
   • Attendance tracking (percentage)
   • Credits completed
   • Study hours per week
   • Extracurricular activities level
   • Internship status

2. Prediction System

   • Weighted prediction model
   • Multiple factor analysis
   • Real-time prediction results
   • Status classification (Likely to Graduate/At Risk)

3. Visualization Dashboard

   • Performance metrics visualization
   • Current vs Target comparison
   • Interactive bar charts
   • Key metrics display

4. Recommendation System

   • Personalized recommendations
   • Performance-based suggestions
   • Dynamic feedback generation

Technical Implementation Details

Technology Stack

• Frontend: Streamlit
• Data Processing: Pandas
• Visualization: Plotly Express
• Prediction Model: Custom weighted algorithm

Model Components

• GPA Weight: 40%
• Attendance Weight: 20%
• Credits Weight: 15%
• Study Hours Weight: 15%
• Extracurricular Activities: 5%
• Internship Experience: 5%

Next Steps

1. Planned Features

   • User authentication system
   • Database integration
   • Historical data tracking
   • Advanced analytics dashboard
   • Export functionality for reports

2. Improvements

   • Enhanced prediction model
   • Additional visualization options
   • More detailed recommendations
   • Performance optimization

Project Structure