This machine learning system analyzes age, academic level, social media usage, platform, sleep hours and academic performance impact to predict student mental health risk level.
Modern frontend with clean sections, animated cards, prediction form, and project based data visualizations.
Uses trained model with scaler and target encoder for prediction output.
Checks usage hours, selected platform and performance impact.
Considers sleep hours and student academic level for better analysis.
The purpose of this project is to help understand how social media habits may affect students. The system takes user input, preprocesses values, scales features and returns a mental health impact prediction.
Sample dashboard style graphs for mental health impact, social media usage and sleep behavior.
Project contact section for university submission and demo presentation.
This website is designed for a machine learning based student mental health prediction system.
Home page, about project, graphs dashboard, contact area and final prediction form are included in one professional HTML template.
Form field names are kept according to your Flask backend.