| import streamlit as st | |
| # Page Title | |
| st.title("🧠 Student Depression Classification") | |
| # Subheader | |
| st.subheader("Welcome to my Machine Learning Project!") | |
| # Introduction | |
| st.markdown(""" | |
| 📌 **Project Introduction:** | |
| This application predicts whether a student is likely to experience depression based on academic, psychological, and lifestyle factors. | |
| The model is trained using a **K-Nearest Neighbors (KNN)** Classifier and deployed through an interactive **Streamlit web interface**. | |
| This project demonstrates the real-world application of machine learning for mental health prediction and awareness. | |
| """) | |
| # Overview | |
| st.markdown(""" | |
| 📚 **Project Overview:** | |
| - Built using **Python**, **Pandas**, **Scikit-learn**, and **Streamlit** | |
| - Machine Learning Algorithm: **K-Nearest Neighbors (KNN) Classifier** | |
| - Trained on a cleaned and preprocessed student mental health dataset | |
| - Includes data cleaning, encoding, scaling, and model evaluation | |
| """) | |
| # Author | |
| st.markdown(""" | |
| 👨💻 **Project by:** | |
| **Sai Praneeth Marripelli** | |
| Postgraduate MCA Student | |
| **Nizam College, Osmania University** | |
| """) | |
| if st.button("Next"): | |
| st.switch_page("pages/1 Problem Statement.py") |