Upload 3 files

app3.py

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+import streamlit as st
+import pandas as pd
+import pickle
+
+st.title('Model that Predict Salary by Experience, Test, Interview :heavy_dollar_sign:')
+model = pickle.load(open('data/maas.pkl', 'rb'))
+
+exp = st.number_input('Experience', 0, 10)
+test = st.number_input('Test', 0, 10)
+interview = st.number_input('Interview', 0, 10)
+if st.button('Predict'):
+    prediction = model.predict([[exp, test, interview]])
+    prediction = round(prediction[0][0], 2)
+    st.success(f'Predicted Salary is {prediction} $')

maas.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:da9cbab516498a8858352d566f3e2107efcef38ee6f5bfa29447b186de3638ac
+size 592

requirements.txt

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+streamlit
+scikit-learn
+pandas