This project is a web-based platform developed for predicting the risk of school dropout among students. It utilizes Angular for the frontend, Flask for the backend, and SQL as the database.

User-friendly interface for inputting student data and obtaining dropout risk predictions. Integration with a machine learning model to provide accurate predictions based on input parameters. Secure authentication system to ensure data privacy and user access control. Efficient data storage and retrieval using SQL database. Visualizations and reporting functionalities to analyze and track dropout risk trends.

Start the frontend:

ng serve Start the backend:

python app.py

Open a web browser and navigate to http://localhost:4200 to access the application.

Register a new account or login with existing credentials. Enter the relevant student information required for the prediction. Click the "Predict" button to obtain the school dropout risk prediction for the entered student. Explore additional features, such as data visualizations and reports, for in-depth analysis of dropout risk trends. Contributing Contributions to the School Dropout Risk Prediction Platform are welcome! If you find any bugs, have suggestions for improvements, or would like to add new features, please submit an issue or create a pull request.