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  1. app.py +76 -0
  2. model_campus +0 -0
app.py ADDED
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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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+
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+
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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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+
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+ try:
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+ model = joblib.load('/Users/nishthapandey/Desktop/PlacementPrediction/model_campus_placement_rf.joblib')
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+ st.success("Model loaded successfully!")
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+ except Exception as e:
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+ st.error(f"Error loading model: {e}")
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+ st.stop()
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+ model = joblib.load(open('/Users/nishthapandey/Desktop/PlacementPrediction/model_campus_placement_rf.joblib','rb'))
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+
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+ def predict_placement(data):
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+ # Preprocess the data
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+ new_data = pd.DataFrame(data)
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+
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+ # Make prediction
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+ prediction = model.predict(new_data)[0]
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+ prob = model.predict_proba(new_data)[0][1]
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+
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+ return prediction, prob
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+
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+ def main():
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+ st.header('Placement Prediciton App')
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+
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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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+ ssc_b = st.radio('Board of Education (SSC)', ['Central', 'Others'])
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+ hsc_p = st.number_input('Higher Secondary Percentage', min_value=0.0, max_value=100.0, value=50.0, step=0.1)
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+ hsc_b = st.radio('Board of Education (HSC)', ['Central', 'Others'])
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+ degree_p = st.number_input('UG 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 Percentage', 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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+
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+ if st.button('predict'):
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+ new_data = {
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+ 'gender': 0 if gender == "Male" else 1,
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+ 'ssc_p': ssc_p,
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+ 'ssc_b': 1 if ssc_b == "Central" else 0,
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+ 'hsc_p': hsc_p,
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+ 'hsc_b': 1 if hsc_b == "Central" else 0,
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+ 'degree_p': degree_p,
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+ 'Branch': 2 if branch == "ECE/EN" else 1 if branch == "CSE" else 0,
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+ 'Workex': 1 if workex == "Yes" else 0,
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+ 'Certifications': certifications,
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+ 'etest_p': etest_p,
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+ 'Backlogs': backlogs,
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+ }
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+
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+ prediction, probability = predict_placement(new_data)
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+ st.write(f'Percentage of getting placed: {probability*100:.2f}%')
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+
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+
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+ if __name__=='__main__':
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+ main()
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+
model_campus ADDED
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