diff --git a/M2/Deep Learning/TP1 - Starter.ipynb b/M2/Deep Learning/TP1 - Starter.ipynb
index 6fb95bb..dd3ec74 100644
--- a/M2/Deep Learning/TP1 - Starter.ipynb	
+++ b/M2/Deep Learning/TP1 - Starter.ipynb	
@@ -487,27 +487,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 421us/step\n",
-      "[5.7584018e-04 4.8742178e-05 9.9363518e-01 4.3561440e-03 2.4410772e-06\n",
-      " 9.6543576e-05 7.6319941e-04 1.7040280e-04 3.4009825e-04 1.1379666e-05]\n",
-      "2\n",
-      "2\n"
+      "\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 712us/step\n",
+      "[9.3210938e-06 9.0745144e-04 9.9405009e-01 1.4055278e-03 5.0518427e-08\n",
+      " 8.1401318e-05 3.4974131e-03 2.3491805e-07 4.7366044e-05 1.1456490e-06]\n"
      ]
     }
    ],
    "source": [
     "predictions = model.predict(X_test)\n",
     "\n",
-    "print(predictions[1])\n",
-    "print(np.argmax(predictions[1]))\n",
-    "print(y_test[1])"
+    "print(predictions[1])"
    ]
   },
   {
@@ -519,19 +515,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[1.0000001 1.        1.        ... 1.0000001 0.9999999 0.9999999]\n"
+      "1.0\n",
+      "2\n",
+      "2\n"
      ]
     }
    ],
    "source": [
-    "print(np.sum(predictions, axis=1))"
+    "print(np.sum(predictions[1]))\n",
+    "print(np.argmax(predictions[1]))\n",
+    "print(y_test[1])"
    ]
   },
   {