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()