From 02009174b386430931f13afbe0b4c13cacd8483e Mon Sep 17 00:00:00 2001
From: User Name <user@example.com>
Date: Sat, 7 Jun 2025 23:27:56 +0200
Subject: [PATCH] init

---
 linear_regression_model.pkl | Bin 0 -> 561 bytes
 requirements.txt            |   7 +++++++
 scaler.pkl                  | Bin 0 -> 943 bytes
 streamlit.py                |  22 ++++++++++++++++++++++
 4 files changed, 29 insertions(+)
 create mode 100644 linear_regression_model.pkl
 create mode 100644 requirements.txt
 create mode 100644 scaler.pkl
 create mode 100644 streamlit.py

diff --git a/linear_regression_model.pkl b/linear_regression_model.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..20da6a5d3238928c3f858a517670118866ba5ea4
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..50eef46
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,7 @@
+
+fastapi
+uvicorn
+joblib
+numpy
+pandas
+scikit-learn
diff --git a/scaler.pkl b/scaler.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..81aebe03c6af86e4f91781f3e4ec80064c051860
GIT binary patch
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literal 0
HcmV?d00001

diff --git a/streamlit.py b/streamlit.py
new file mode 100644
index 0000000..bb8c693
--- /dev/null
+++ b/streamlit.py
@@ -0,0 +1,22 @@
+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}")