diff --git a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb
index b5b726f2146456a9a8bd82ca52c1e0f389b1da63..3d7051f5b30a6b5faf0acfdc6d2e80d368e7509f 100644
--- a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb	
+++ b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb	
@@ -4106,8 +4106,7 @@
     "\n",
     "\n",
     "Given an image like the example below, our goal is to generate a caption such as \"a surfer riding on a wave\".\n",
-    "\n",
-    "![alt text](./Bilder/surf.jpg \"Title\")"
+    "<img src=\"./Bilder/surf.jpg\" width=\"600\">\n"
    ]
   },
   {
@@ -4116,8 +4115,7 @@
    "source": [
     "To accomplish this, you'll use an attention-based model, which enables us to see what parts of the image the model focuses on as it generates a caption.\n",
     "\n",
-    "\n",
-    "![alt text](./Bilder/imcap_prediction.png \"Title\")\n"
+    "<img src=\"./Bilder/imcap_prediction.png\" width=\"600\">\n"
    ]
   },
   {
@@ -5050,7 +5048,7 @@
     }
    ],
    "source": [
-    "image = './Bilder/nachknast.jpg'\n",
+    "image = './Bilder/example_10.jpg'\n",
     "result, attention_plot = evaluate(image)\n",
     "print ('Prediction Caption:', ' '.join(result))\n",
     "plot_attention(image, result, attention_plot)\n",