small change in 03_ml_basics_simple_neural_network.ipynb

notebooks/03_ml_basics_simple_neural_network.ipynb

@@ -23,6 +23,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -76,7 +77,7 @@
     "\n",
     "Note, that it is assumed that the activation function is a sigmoid with the derivative\n",
     "\n",
-    "$$ \\sigma(x) * (1 - \\sigma(x)) $$\n",
+    "$$ \\sigma(x) \\cdot (1 - \\sigma(x)) $$\n",
     "\n",
     "Applying the chain rule further, we obtain the gradient for the weights from the input layer to the hidden layer: \n",
     "\n",