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