Making it stylistically similar to the other DS demo (#1)

- Making it stylistically similar to the other DS demo (209c7e7b2619a0152e33fbf4dc640dfc96fc630f)


Co-authored-by: Abubakar Abid <[email protected]>

app.py

@@ -67,12 +67,7 @@ unique_country = sorted(X_train["native.country"].unique())
 
 with gr.Blocks() as demo:
     gr.Markdown("""
-    # Income Classification with XGBoost 💰
-    
-    This example shows how to load data from the hugging face hub to train an XGBoost classifier and
-    demo the predictions with gradio.
-
-    The source is [here](https://huggingface.co/spaces/gradio/xgboost-income-prediction-with-explainability).
+    **Income Classification with XGBoost 💰**:  This demo uses an XGBoost classifier predicts income based on demographic factors, along with Shapley value-based *explanations*. The [source code for this Gradio demo is here](https://huggingface.co/spaces/gradio/xgboost-income-prediction-with-explainability).
     """)
     with gr.Row():
         with gr.Column():
@@ -135,7 +130,7 @@ with gr.Blocks() as demo:
             plot = gr.Plot()
             with gr.Row():
                 predict_btn = gr.Button(value="Predict")
-                interpret_btn = gr.Button(value="Interpret")
+                interpret_btn = gr.Button(value="Explain")
             predict_btn.click(
                 predict,
                 inputs=[