diff --git a/site/en/r1/tutorials/keras/basic_classification.ipynb b/site/en/r1/tutorials/keras/basic_classification.ipynb
index 14950538ce4..53f9f536ab0 100644
--- a/site/en/r1/tutorials/keras/basic_classification.ipynb
+++ b/site/en/r1/tutorials/keras/basic_classification.ipynb
@@ -728,6 +728,7 @@
         "plot_image(i, predictions[i], test_labels, test_images)\n",
         "plt.subplot(1,2,2)\n",
         "plot_value_array(i, predictions[i],  test_labels)\n",
+        "plt.xticks(range(10), class_names, rotation=45, fontsize=6)\n",
         "plt.show()"
       ]
     },
@@ -745,6 +746,7 @@
         "plot_image(i, predictions[i], test_labels, test_images)\n",
         "plt.subplot(1,2,2)\n",
         "plot_value_array(i, predictions[i],  test_labels)\n",
+        "plt.xticks(range(10), class_names, rotation=45, fontsize=6)\n",
         "plt.show()"
       ]
     },
@@ -779,6 +781,45 @@
         "plt.show()"
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Display 6 incorrect predictions and 6 correct predictions\n",
+        "num_incorrect = 6\n",
+        "num_correct = 6 \n",
+        "\n",
+        "incorrect_indices = []\n",
+        "correct_indices = []\n",
+        "\n",
+        "# Find correct and incorrect predictions\n",
+        "for i in range(len(test_labels)):\n",
+        "    predicted_label = np.argmax(predictions[i])\n",
+        "    true_label = test_labels[i]\n",
+        "    if predicted_label != true_label and len(incorrect_indices) < num_incorrect:\n",
+        "        incorrect_indices.append(i)\n",
+        "    elif predicted_label == true_label and len(correct_indices) < num_correct:\n",
+        "        correct_indices.append(i)\n",
+        "    # Stop when both lists have enough examples\n",
+        "    if len(incorrect_indices) == num_incorrect and len(correct_indices) == num_correct:\n",
+        "        break\n",
+        "\n",
+        "selected_indices = incorrect_indices + correct_indices\n",
+        "num_images = len(selected_indices)\n",
+        "\n",
+        "num_rows = 5  \n",
+        "num_cols = 3 \n",
+        "plt.figure(figsize=(2 * 2 * num_cols, 2 * num_rows))\n",
+        "for i, idx in enumerate(selected_indices):\n",
+        "    plt.subplot(num_rows, 2 * num_cols, 2 * i + 1)\n",
+        "    plot_image(idx, predictions[idx], test_labels, test_images)\n",
+        "    plt.subplot(num_rows, 2 * num_cols, 2 * i + 2)\n",
+        "    plot_value_array(idx, predictions[idx], test_labels)\n",
+        "plt.show()"
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {