Upload 3 files

app.py

@@ -0,0 +1,37 @@
+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")

demo.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:013b1257c3612ccfb256ea0cb34e0947bffa7e2bb96a1421f7dd99c82bab8f7d
+size 2339007

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+scikit-learn
+pandas
+numpy