diff --git a/13_convolutional_neural_networks.ipynb b/13_convolutional_neural_networks.ipynb
index b4ea324..7cd118d 100644
--- a/13_convolutional_neural_networks.ipynb
+++ b/13_convolutional_neural_networks.ipynb
@@ -124,9 +124,9 @@
    },
    "outputs": [],
    "source": [
-    "from sklearn.datasets import load_sample_images\n",
-    "dataset = load_sample_images()\n",
-    "china, flower = dataset.images\n",
+    "from sklearn.datasets import load_sample_image\n",
+    "china = load_sample_image(\"china.jpg\")\n",
+    "flower = load_sample_image(\"flower.jpg\")\n",
     "image = china[150:220, 130:250]\n",
     "height, width, channels = image.shape\n",
     "image_grayscale = image.mean(axis=2).astype(np.float32)\n",
@@ -232,8 +232,7 @@
    },
    "outputs": [],
    "source": [
-    "from sklearn.datasets import load_sample_images\n",
-    "dataset = np.array(load_sample_images().images, dtype=np.float32)\n",
+    "dataset = np.array([china, flower], dtype=np.float32)\n",
     "batch_size, height, width, channels = dataset.shape\n",
     "\n",
     "filters = np.zeros(shape=(7, 7, channels, 2), dtype=np.float32)\n",
@@ -261,7 +260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
@@ -283,7 +282,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
@@ -307,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },