Upload 5 files

app.py

@@ -0,0 +1,46 @@
+
+import pandas as pd
+import gradio as gr
+import joblib
+
+std=joblib.load('std_col.pkl')
+lr=joblib.load('model.pkl')
+
+
+std_col=['GPA', 'Test Score', 'Extracurricular Activities', 'Volunteer Hours','Recommendation Letters', 'Essay Score']
+
+
+
+
+def predict_admission(gpa, ts, ea, vh, rl, es):
+  try:
+    input_data = pd.DataFrame(
+        {
+            "GPA":[gpa],
+            "Test Score":[ts],
+            "Extracurricular Activities":[ea],
+            "Volunteer Hours":[vh],
+            "Recommendation Letters":[rl],
+            "Essay Score":[es]}
+    )
+
+    input_data[std_col]=std.transform(input_data[std_col])
+    prediction = lr.predict(input_data)
+    if prediction[0] == 0:
+          return "No"
+    else:
+          return "Yes"
+  except Exception as e:
+        return str(e)
+gr.Interface(
+    inputs= [
+
+             gr.Number(label="GPA"),
+             gr.Number(label="Test Score"),
+             gr.Number(label="Extracurricular Activities"),
+             gr.Number(label="Volunteer Hours"),
+             gr.Number(label="Recommendation Letters"),
+             gr.Number(label="Essay Score")
+    ],
+    fn = predict_admission, outputs= gr.Textbox(label="Admission Decision")
+).launch()

le_col.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:afebf6c623345666acc74c154973995bd849136a8a03e8afcec6623aebff9e64
+size 360

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72f77b1d17dab96a69ae44593a885198d56a540d1c53abdc1034b6ca3fb44a9c
+size 1343

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+pandas
+joblib
+scikit-learn

std_col.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:82f9d6b8512df3d5eec72b4e4fa27440fa579256341463178448eff416533d3e
+size 1175