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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+banner.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,40 @@
+import numpy as np
+import streamlit as st
+import joblib
+
+logo_url = "logo.png"
+banner_path = "banner.jpg"
+
+col1, col2= st.columns([1, 3])
+with col1:
+   st.image(logo_url, width = 100)
+with col2:
+   st.write("# Acko Insurance App")
+
+st.image(banner_path)
+
+age = st.number_input("Enter your age", step = 1)
+height_ft = st.number_input("Enter feet part of your height", step = 1,value = 5)
+height_inch = st.number_input("Enter inch part of your height", step = 1, value = 5)
+weight_kg = st.number_input("Enter your weight in KG")
+height_meter = height_ft *0.3048 + height_inch*0.0254
+bmi = round(weight_kg/height_meter**2,2)
+smoker = st.selectbox(
+    "Enter your smoking status?",
+    ("yes", "no"))
+children = st.selectbox(
+   "Enter Number of children",
+   (0,1,2,3,4))
+
+test_data = np.array([[age, bmi, smoker, children]])
+st.write(test_data)
+
+# load model
+model = joblib.load("insurance_joblib")
+
+# predict button
+if st.button("Predict"):
+   y_pred = model.predict(test_data)
+   amount = np.round(y_pred**2,2)[0]
+   st.write(f"## Your Insurance Premium amount is: ${amount}")
+

requirements.txt

@@ -0,0 +1,4 @@
+numpy ==1.26.4
+scikit-learn ==1.5.2
+joblib ==1.4.2
+streamlit ==1.39.0