🎓 Student Performance Predictor

A full-stack Machine Learning web application that predicts student academic performance based on attendance, study hours, internal marks, and assignment scores.

The platform includes secure authentication, personalized prediction history, interactive analytics dashboards, and real-time data visualization — all deployed as a live web application.

---

🚀 Live Demo

🌐 https://student-performance-predictor-1mlt.onrender.com

---

✨ Features

• 🔐 Secure User Authentication (Signup / Login / Logout)
• 🔒 Password Hashing using Werkzeug Security
• 📊 Student Performance Prediction using Machine Learning
• 🧠 Linear Regression Model using Scikit-learn
• 📈 Interactive Analytics Dashboard with Trendline Graphs
• 📉 Real-Time Data Visualization using Plotly
• 👤 User-Specific Prediction History
• 🗂️ SQLite Database Integration
• 📱 Responsive Modern Dashboard UI
• 🌐 Fully Deployed Flask Web Application
• 🚀 GitHub + Render Deployment Integration

---

🧠 How It Works

The application collects:

• Attendance Percentage
• Study Hours
• Internal Marks
• Assignment Scores

These inputs are passed into a trained Linear Regression model built using Scikit-learn, which predicts the student's final academic score.

Predictions are then:

• stored in a SQLite database
• visualized using Plotly graphs
• displayed in a personalized analytics dashboard

---

🛠️ Tech Stack

Frontend

• HTML
• CSS

Backend

• Flask
• SQLite

Machine Learning

• Scikit-learn
• Pandas
• NumPy
• Statsmodels

Data Visualization

• Plotly

Authentication & Security

• Werkzeug Password Hashing

Deployment

• Render
• GitHub

---

📂 Project Structure

student-performance-predictor/
│
├── app.py
├── requirements.txt
├── predictions.db
├── student_data.csv
│
├── static/
│   └── style.css
│
├── templates/
│   ├── index.html
│   ├── login.html
│   └── signup.html
│
└── README.md

---

📷 Screenshots

🏠 Dashboard

🔐 Login Page

📝 Signup Page

---

⚙️ Installation

Clone Repository

git clone https://github.com/AnushreeKasturi/student-performance-predictor.git

Navigate to Project Folder

cd student-performance-predictor

Install Dependencies

pip install -r requirements.txt

Run Application

python app.py

---

🚀 Future Improvements

• AI-based academic recommendations
• PDF report generation
• Advanced analytics dashboard
• Dark/Light mode toggle
• Performance trend tracking
• Email notifications

---

👩‍💻 Author

Anushree Kasturi

GitHub: https://github.com/AnushreeKasturi

---