Upload 5 files

.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 +1,36 @@
+import streamlit as st
+import numpy as np
+import joblib
+
+st.title("Premium prediction app")
+
+st.image("banner.jpg")
+
+age = st.number_input("Enter your age", value  = 30, step = 1)
+gender = st.selectbox(label = "Select gender", options = ["Male", "Female"])
+bmi = st.number_input("enter your bmi", value = 22.1, step = .1)
+children = st.selectbox(label = "Select number of children", options = [0,1,2,3,4,5])
+smoker = st.selectbox(label = "Smoking status", options = ["yes", "no"])
+
+gender_num = 0 if gender == "Male" else 1
+smoker_num = 0 if smoker == "no" else 1
+
+test_data = np.array([[age, bmi, children, smoker_num]])
+
+poly = joblib.load("poly_obj")
+model = joblib.load("insurance_joblib")
+
+submit_bn = st.button("Submit")
+
+if submit_bn:
+
+
+    test_poly = poly.transform(test_data)
+
+    y_pred_log = model.predict(test_poly)
+
+    y_pred = np.exp(y_pred_log)
+    st.write(f"## Insurance Premium Amount: ${np.round(y_pred[0], 2)}")
+
+
+

requirements.txt

@@ -0,0 +1,4 @@
+streamlit == 1.36.0
+numpy == 1.26.4
+joblib == 1.4.2
+scikit-learn == 1.5.0