Create app.py

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn.model_selection import train_test_split
+from sklearn.datasets import load_breast_cancer
+from sklearn.tree import DecisionTreeClassifier
+
+theme = gr.themes.Monochrome(
+    primary_hue="indigo",
+    secondary_hue="blue",
+    neutral_hue="slate",
+)
+
+description = f"""
+## Description
+This demo can be used to evaluate the ability of k-means initializations strategies to make the algorithm convergence robust
+"""
+
+with gr.Blocks(theme=theme) as demo:
+    gr.Markdown('''
+            <div>
+            <h1 style='text-align: center'>Empirical evaluation of the impact of k-means initialization 📊</h1>
+            </div>
+        ''')
+    gr.Markdown(description)
+
+demo.launch()