Update pages/14_SVM.py

pages/14_SVM.py

@@ -63,9 +63,8 @@ elif section == "📐 Mathematical Formulation":
     st.markdown("### Soft Margin Condition:")
     st.latex(r"y_i (w^T x_i + b) \geq 1 - \xi_i")
 
-    st.markdown("### Slack Variable Interpretation:")
-    st.markdown(r"$\xi_i$")
-    st.write("""
+    st.markdown(r"### Slack Variable \( \xi_i \) Interpretation:")
+    st.write(r"""
     - \( \xi_i = 0 \): Correct and outside the margin  
     - \( 0 < \xi_i \leq 1 \): Inside the margin, but correctly classified  
     - \( \xi_i > 1 \): Misclassified
@@ -86,7 +85,7 @@ elif section == "✅ Pros & Cons of SVM":
     """)
 
 elif section == "🔄 Dual Form & Kernel Trick":
-    st.markdown("""
+    st.markdown(r"""
     When data is not linearly separable in its original space, we use the **kernel trick** to transform it.
     
     ### Common Kernels: