diff --git a/wyk/12_Propagacja_wsteczna.ipynb b/wyk/12_Propagacja_wsteczna.ipynb
index c8da3e3..8f4f945 100644
--- a/wyk/12_Propagacja_wsteczna.ipynb
+++ b/wyk/12_Propagacja_wsteczna.ipynb
@@ -260,8 +260,8 @@
     }
    },
    "source": [
-    "$$ f(x_1, x_2) = \\max(x_1 + x_2) \\hskip{12em} \\\\\n",
-    "\\to \\qquad \\frac{\\partial f}{\\partial x_1} = \\mathbb{1}_{x \\geq y}, \\quad \\frac{\\partial f}{\\partial x_2} = \\mathbb{1}_{y \\geq x}, \\quad \\nabla f = (\\mathbb{1}_{x \\geq y}, \\mathbb{1}_{y \\geq x}) $$ "
+    "$$ f(x_1, x_2) = \\max(x_1, x_2) \\hskip{12em} \\\\\n",
+    "\\to \\qquad \\frac{\\partial f}{\\partial x_1} = \\mathbb{1}_{x_1 \\geq x_2}, \\quad \\frac{\\partial f}{\\partial x_2} = \\mathbb{1}_{x_2 \\geq x_1}, \\quad \\nabla f = (\\mathbb{1}_{x_1 \\geq x_2}, \\mathbb{1}_{x_2 \\geq x_1}) $$ "
    ]
   },
   {
@@ -1085,9 +1085,9 @@
    "source": [
     "model = keras.Sequential()\n",
     "model.add(Dense(512, activation=\"relu\", input_shape=(784,)))\n",
-    "# model.add(Dropout(0.2))\n",
+    "model.add(Dropout(0.2))\n",
     "model.add(Dense(512, activation=\"relu\"))\n",
-    "# model.add(Dropout(0.2))\n",
+    "model.add(Dropout(0.2))\n",
     "model.add(Dense(num_classes, activation=\"softmax\"))\n",
     "model.summary()"
    ]