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import streamlit as st
import pandas as pd
import numpy as np
import joblib
# Load the trained model
model = joblib.load('student_performance_model.h5')
# Define the input features
def predict_marks(Hours_Studied,Previous_Scores,Extracurricular_Activities,Sleep_Hours,Sample_Question_Papers_Practiced):
input_data = np.array([[Hours_Studied,Previous_Scores,Extracurricular_Activities,Sleep_Hours,Sample_Question_Papers_Practiced]])
prediction = model.predict(input_data)
prediction = round(float(prediction), 2)
if prediction >= 100:
prediction = 100
return prediction
# Display the app title
def main():
st.title("Student Performance Prediction")
name = st.text_input("Enter your name:--")
Hours_Studied = st.number_input("Enter Number of hours you daily study:--",max_value=12,min_value=0,value=0)
Previous_Scores = st.number_input("Enter your previous scores:--",max_value=100.0,min_value=0.0,value=0.0)
Extracurricular_Activities = st.number_input("Enter the number of extracurricular activities you participate in:--",max_value=10,min_value=0,value=0)
Sleep_Hours= st.number_input("Enter the number of hours you sleep daily:--",max_value=12,min_value=0,value=0)
Sample_Question_Papers_Practiced= st.number_input("Enter the number of sample question papers you practice:--",max_value=100,min_value=0,value=0)
st.sidebar.title("Prediction")
st.sidebar.write(f"Hey, {name}")
if st.button("Result"):
prediction = predict_marks(Hours_Studied,Previous_Scores,Extracurricular_Activities,Sleep_Hours,Sample_Question_Papers_Practiced)
if prediction > 90:
st.success(f"Your predicted grade is A you are on a correct path with the estimated score of {prediction}.")
st.balloons()
elif prediction > 35:
st.warning(f"Your predicted grade is B you need to impove your estimated score is {prediction}.")
else:
st.error(f"Work hard your estimated score is {prediction}.")
if __name__ == "__main__":
main()
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