init

requirements.txt

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+
+fastapi
+uvicorn
+joblib
+numpy
+pandas
+scikit-learn

streamlit.py

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+import streamlit as st
+import joblib
+
+# Load the model and scaler
+model = joblib.load("linear_regression_model.pkl")
+scaler = joblib.load("scaler.pkl")
+
+# Streamlit app
+st.title("MetaBrains Student Test Score Predictor")
+st.write("Enter the number of hours studied to predict the test score.")
+
+# User input
+hours = st.number_input("Hours studied:", min_value=0.0, step=1.0)
+
+if st.button("Predict"):
+    try:
+        data = [[hours]]
+        scaled_data = scaler.transform(data)
+        prediction = model.predict(scaled_data)
+        st.write(f"Predicted Test Score: {prediction[0]:.2f}")
+    except Exception as e:
+        st.error(f"Error: {e}")