Update app.py

app.py

@@ -1,24 +1,17 @@
 import streamlit as st 
 import joblib
 import pandas as pd
-#st.title('Placement Prediction app')
-# st.markdown("""
-#     <style>
-#     .title {
-#         font-size: 50px;
-#         font-weight: bold;
-#         color: #4CAF50;
-#         text-align: center;
-#         font-family: 'Courier New', Courier, monospace;
-#     }
-#     </style>
-#     """, unsafe_allow_html=True)
-
-
-# st.title('Placement Prediction App')
-# st.subheader('Predicting student placement outcomes using machine learning')
-# st.markdown('This app uses historical data to predict whether a student will be placed in a company based on their profile.')
 
+st.markdown(
+    """
+    <style>
+    body {
+        background-color: #C9E4DE; 
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
 try:
     model = joblib.load('model_campus')
     st.success("Model loaded successfully!")
@@ -39,6 +32,7 @@ def predict_placement(data):
 
 def main():
     st.header('Placement Prediciton App')
+    st.markdown('This app uses historical data to predict whether a student will be placed in a company based on their profile.')
 
     gender = st.radio('Gender', ['Male', 'Female'])
     ssc_p = st.number_input('Secondary School Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
@@ -49,7 +43,7 @@ def main():
     branch = st.selectbox('Branch of Study', ['CSE', 'ECE/EN', 'Others'])
     workex = st.radio('Work Experience', ['Yes', 'No'])
     certifications = st.number_input('Number of Certifications', min_value=0, max_value=10, value=0)
-    etest_p = st.number_input('Employability Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
+    etest_p = st.number_input('Employability Test Score', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
     backlogs = st.number_input('Number of Backlogs', min_value=0, max_value=10, value=0)
     
     if st.button('predict'):