Create inference.py

inference.py

@@ -0,0 +1,24 @@
+import joblib
+import pandas as pd
+
+model = joblib.load("best_random_forest_model.joblib")
+scaler = joblib.load("std_scaler.bin")
+
+def predict(data):
+
+    df = pd.DataFrame(
+        data,
+        columns=[
+            "LoanOriginalAmount",
+            "CreditScoreRangeLower",
+            "StatedMonthlyIncome",
+            "Investors",
+            "MonthlyLoanPayment",
+        ],
+    )
+
+    scaled = scaler.transform(df.values)
+
+    prediction = model.predict(scaled)
+
+    return prediction.tolist()