Upload 3 files

app.py

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+import streamlit as st
+import pandas as pd
+from sklearn.ensemble import RandomForestClassifier
+from joblib import load
+
+st.title("Tabular Data Sentiment Analysis")
+
+model = load('random_forest_model.joblib')
+
+df = pd.DataFrame(
+    [{'product_id': 30,
+  'Review_Length': 252,
+  'Rating': 4,
+  'Avg_Word_Length': 5,
+  'Times_purchased': 13,
+  'unique_words': 40}])
+
+edited_df = st.data_editor(df, num_rows="dynamic")
+
+if st.button("Predict Sentiment", type="primary"):
+    output = model.predict(edited_df)
+    edited_df['predicted sentiment'] = output
+    edited_df['predicted sentiment'].replace({0:"Positive", 1:"Negative"}, inplace=True)
+    st.text(edited_df)
+

random_forest_model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e35b91803dba1eeaa4bce6debda9f91457b09c7a45e8daee4d2ff9f086925dbe
+size 5876137