diff --git a/examples/models-usages/generation/gan-image-generation/conditional_gan_mnist.ipynb b/examples/models-usages/generation/gan-image-generation/conditional_gan_mnist.ipynb
index a2f3b42..c4baa9e 100644
--- a/examples/models-usages/generation/gan-image-generation/conditional_gan_mnist.ipynb
+++ b/examples/models-usages/generation/gan-image-generation/conditional_gan_mnist.ipynb
@@ -15,7 +15,7 @@
     "from keras.datasets import mnist\n",
     "from IPython.display import Image as IPImage\n",
     "\n",
-    "from neuralnetlib.preprocessing import one_hot_encode\n",
+    "from neuralnetlib.preprocessing import one_hot_encode, MinMaxScaler\n",
     "from neuralnetlib.models import Sequential, GAN\n",
     "from neuralnetlib.layers import Input, Dense, BatchNormalization, Dropout\n",
     "from neuralnetlib.optimizers import Adam"
@@ -39,7 +39,8 @@
     "X = X.reshape(X.shape[0], -1)\n",
     "\n",
     "# Normalize pixel values\n",
-    "X = X.astype('float32') / 255\n",
+    "scaler = MinMaxScaler(feature_range=(-1, 1))\n",
+    "X = scaler.fit_transform(X)\n",
     "\n",
     "# Labels to categorical \n",
     "y = one_hot_encode(y, n_classes)"
@@ -84,7 +85,7 @@
     "generator.add(BatchNormalization())\n",
     "generator.add(Dense(1024, activation='leakyrelu'))\n",
     "generator.add(BatchNormalization())\n",
-    "generator.add(Dense(784, activation='sigmoid'))"
+    "generator.add(Dense(784, activation='tanh'))"
    ]
   },
   {