diff --git a/04_training_linear_models.ipynb b/04_training_linear_models.ipynb
index 8632638..061ff7f 100644
--- a/04_training_linear_models.ipynb
+++ b/04_training_linear_models.ipynb
@@ -1068,7 +1068,7 @@
     }
    ],
    "source": [
-    "# extra code – this cell generates Figure 4–17\n",
+    "# extra code – this cell generates Figure 4–18\n",
     "\n",
     "def plot_model(model_class, polynomial, alphas, **model_kwargs):\n",
     "    plt.plot(X, y, \"b.\", linewidth=3)\n",
@@ -1243,7 +1243,7 @@
     }
    ],
    "source": [
-    "# extra code – this cell generates Figure 4–18\n",
+    "# extra code – this cell generates Figure 4–19\n",
     "plt.figure(figsize=(9, 3.5))\n",
     "plt.subplot(121)\n",
     "plot_model(Lasso, polynomial=False, alphas=(0, 0.1, 1), random_state=42)\n",
@@ -1272,7 +1272,7 @@
     }
    ],
    "source": [
-    "# extra code – this BIG cell generates Figure 4–19\n",
+    "# extra code – this BIG cell generates Figure 4–20\n",
     "\n",
     "t1a, t1b, t2a, t2b = -1, 3, -1.5, 1.5\n",
     "\n",
@@ -1448,7 +1448,7 @@
     "    val_errors.append(val_error)\n",
     "    train_errors.append(train_error)\n",
     "\n",
-    "# extra code – this section generates Figure 4–20\n",
+    "# extra code – this section generates Figure 4–21\n",
     "best_epoch = np.argmin(val_errors)\n",
     "plt.figure(figsize=(6, 4))\n",
     "plt.annotate('Best model',\n",
@@ -1500,7 +1500,7 @@
     }
    ],
    "source": [
-    "# extra code – generates Figure 4–21\n",
+    "# extra code – generates Figure 4–22\n",
     "\n",
     "lim = 6\n",
     "t = np.linspace(-lim, lim, 100)\n",