Upload 3 files

app.py

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+import streamlit as st
+from tensorflow.keras.models import load_model
+import numpy as np
+from sklearn.preprocessing import scale
+
+model=load_model("model.h5")
+
+st.write("Learn Your Credit State")
+
+age=st.number_input("Your Age",min_value=18)
+mi=st.number_input("Monthl Income")
+debt_ratio=st.number_input("Debt Ratio")
+ruoul=st.number_input("Revolving Utilization of Unsecured Lines")
+data=[age,mi, debt_ratio,ruoul]
+if st.button("Predict"):
+    data=np.array(data)
+    if len(data.shape) == 1:
+       data = np.expand_dims(data, axis=0)
+       data=scale(data) 
+       prediction=model.predict(data)
+       predicted_class=np.argmax(prediction)
+       class_names=["No","Yes"]
+       st.write(class_names[predicted_class])

model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:055d81ce2350a8017a7a71a99a012c1f1604f7f55f32c2a7a6625f26e2f7f46c
+size 168800

requirements.txt

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+tensorflow
+sciit-learn
+numpy
+streamlit