add files

app.py

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+import streamlit as st
+import pandas as pd
+import pickle
+
+st.title("--Insert title here--")
+
+# Step 1 - import saved model
+model = pickle.load(open("milk_pred.pkl", "rb"))
+
+st.write('Insert feature to predict')
+
+# Step 2 - prepare input data for user
+ph = st.slider(label='pH', min_value=3.0, max_value=9.5, value=6.5, step=0.1)
+temp = st.slider(label='Temprature', min_value=34, max_value=90, value=40, step=1)
+taste = st.selectbox(label='Taste', options=['Good', 'Bad'], key=1)
+odor = st.selectbox(label='Odor', options=['Good', 'Bad'])
+fat = st.selectbox(label='Fat', options=['High', 'Low'])
+turb = st.selectbox(label='Turbidity', options=['High', 'Low'])
+color = st.number_input(label='Colour', min_value=240, max_value=255, value=245, step=1)
+
+# convert into dataframe
+data = pd.DataFrame({'pH': [ph],
+                'Temprature': [temp],
+                'Taste': [taste],
+                'Odor':[odor],
+                'Fat': [fat],
+                'Turbidity': [turb],
+                'Colour': [color]
+                })
+st.write(data)
+# model predict
+clas = model.predict(data).tolist()[0]
+
+# interpretation
+st.write('Classification Result: ')
+if clas == 0:
+    st.text('Low')
+elif clas == 1:
+    st.text('Medium')
+else:
+    st.text('High')
+
+

milk_pred.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3b2f76b67e9b8663a9598ea2cde68a0ee9f88cef6e82e93fc44c32c249687568
+size 271620

requirements.txt

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+streamlit
+pandas
+scikit-learn==1.0.2
+feature_engine==1.5.1