Add ML intuitions py file

app.py

@@ -188,7 +188,33 @@ def main():
 
         # Show plot in Streamlit
         st.pyplot(fig)    
-    
+        
+        st.markdown("""
+        When the classes are heavily **intertwined** and not linearly separable, **Logistic Regression** struggles to draw a good boundary. Here's a demonstration.
+        """)
+        
+        # Generate an intertwined dataset
+        X, y = make_classification(
+            n_samples=200,
+            n_features=2,
+            n_redundant=0,
+            n_informative=2,
+            n_clusters_per_class=2,
+            class_sep=0.3,  # Low separation
+            flip_y=0.1,     # Add some label noise
+            random_state=42
+        )
+        
+        # Train logistic regression
+        clf = make_pipeline(StandardScaler(), LogisticRegression())
+        clf.fit(X, y)
+
+        # Plot
+        fig, ax = plt.subplots(figsize=(8, 6))
+        plot_decision_boundary(clf, X, y, ax)
+        ax.set_title("Logistic Regression Decision Boundary - intertwined classes")
+        st.pyplot(fig)
+            
         
     # feature discriminatio
     # Load dataset