life cycle of ml page added

pages/03_life_cycle_of_ml_project.py

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+import matplotlib.pyplot as plt
+import numpy as np
+
+def draw_lifecycle_diagram():
+    # Labels and colors for the lifecycle phases
+    labels = [
+        "1. Gathering Data", 
+        "2. Data Preparation", 
+        "3. Data Wrangling", 
+        "4. Analyze Data", 
+        "5. Train Model", 
+        "6. Test Model", 
+        "7. Deployment"
+    ]
+    colors = [
+        "#3CB371", "#8FBC8F", "#00CED1", "#1E90FF", 
+        "#6A5ACD", "#FF8C00", "#DC143C"
+    ]
+
+    # Create a figure and axis with equal aspect ratio
+    fig, ax = plt.subplots(figsize=(9, 9), subplot_kw={"aspect": "equal"})
+    size = 0.3  # Width of the pie sections
+
+    # Create pie sections for the lifecycle phases
+    wedges, _ = ax.pie(
+        [1] * len(labels), 
+        colors=colors, 
+        radius=1, 
+        startangle=90, 
+        wedgeprops=dict(width=size, edgecolor='w')
+    )
+
+    # Add text labels around the circle
+    for i, wedge in enumerate(wedges):
+        # Calculate the angle for the label placement
+        angle = (wedge.theta2 - wedge.theta1) / 2.0 + wedge.theta1
+        x = np.cos(np.deg2rad(angle))
+        y = np.sin(np.deg2rad(angle))
+
+        # Add label text
+        ax.text(
+            1.2 * x, 1.2 * y, labels[i],
+            ha="center", va="center", fontsize=10, weight="bold",
+            bbox=dict(boxstyle="round,pad=0.3", facecolor=colors[i], edgecolor="w")
+        )
+
+    # Add center text with a descriptive title
+    ax.text(
+        0, 0, "Machine Learning\nLifecycle", 
+        ha="center", va="center", fontsize=16, weight="bold", color="black",
+        bbox=dict(boxstyle="round,pad=0.5", facecolor="white", edgecolor="black")
+    )
+
+    # Clean up the diagram style
+    ax.set(aspect="equal", xticks=[], yticks=[], title="Machine Learning Lifecycle")
+    return fig
+
+# Save the diagram or display it in Streamlit
+if __name__ == "__main__":
+    # Display the diagram
+    fig = draw_lifecycle_diagram()
+    plt.show()