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71a7fb2
1
Parent(s):
a71b7de
overview updates
Browse files
app.py
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@@ -29,7 +29,22 @@ X_names = [
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# Title
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st.title("Uplift Modeling in Retail Demo")
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tabs = st.sidebar.radio("Navigation", [
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if tabs == "Data generation":
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# Title
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st.title("Uplift Modeling in Retail Demo")
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tabs = st.sidebar.radio("Navigation", [
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"Overview"
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"Data generation",
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"Exploratory analysis",
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"Model training",
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"Economic effects"]
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)
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if tabs == "Overview":
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st.header("Overview")
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st.write("""
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This app demonstrates the use of uplift modeling to understand the effect of different actions (like promotions) on customer behavior. We generate a simulated dataset and use it to train a model that predicts the uplift effect of different treatments on customer behavior. We then evaluate the model using the Qini curve, which measures the uplift effect of a model compared to a random model.
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""")
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# embed Loom video on the page
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st.video("https://www.loom.com/share/57591e60cf7a44fdb8de5d7fb66808e8")
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st.write("To get started, select the 'Data generation' tab from the sidebar.")
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if tabs == "Data generation":
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