diff --git a/Notebooks/Chap07/7_1_Backpropagation_in_Toy_Model.ipynb b/Notebooks/Chap07/7_1_Backpropagation_in_Toy_Model.ipynb
index 728ab175..1dd8bb02 100644
--- a/Notebooks/Chap07/7_1_Backpropagation_in_Toy_Model.ipynb
+++ b/Notebooks/Chap07/7_1_Backpropagation_in_Toy_Model.ipynb
@@ -4,7 +4,7 @@
   "metadata": {
     "colab": {
       "provenance": [],
-      "authorship_tag": "ABX9TyOwOpROPBel8eYGzp5DGRkt",
+      "authorship_tag": "ABX9TyP5wHK5E7/el+vxU947K3q8",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -55,7 +55,7 @@
         "This is a composition of the functions $\\cos[\\bullet],\\exp[\\bullet],\\sin[\\bullet]$.   I chose these just because you probably already know the derivatives of these functions:\n",
         "\n",
         "\\begin{eqnarray*}\n",
-        " \\frac{\\partial \\cos[z]}{\\partial z} = -\\sin[z] \\quad\\quad \\frac{\\partial \\exp[z]}{\\partial z} = \\exp[z] \\quad\\quad \\frac{\\partial \\sin[z]}{\\partial z} = -\\cos[z].\n",
+        " \\frac{\\partial \\cos[z]}{\\partial z} = -\\sin[z] \\quad\\quad \\frac{\\partial \\exp[z]}{\\partial z} = \\exp[z] \\quad\\quad \\frac{\\partial \\sin[z]}{\\partial z} = \\cos[z].\n",
         "\\end{eqnarray*}\n",
         "\n",
         "Suppose that we have a least squares loss function:\n",
@@ -107,8 +107,8 @@
         "  return beta3+omega3 * np.cos(beta2 + omega2 * np.exp(beta1 + omega1 * np.sin(beta0 + omega0 * x)))\n",
         "\n",
         "def likelihood(x, y, beta0, beta1, beta2, beta3, omega0, omega1, omega2, omega3):\n",
-        "  diff = fn(x, beta0, beta1, beta2, beta3, omega0, omega1, omega2, omega3) - y ;\n",
-        "  return diff * diff ;"
+        "  diff = fn(x, beta0, beta1, beta2, beta3, omega0, omega1, omega2, omega3) - y\n",
+        "  return diff * diff"
       ]
     },
     {
@@ -123,8 +123,8 @@
     {
       "cell_type": "code",
       "source": [
-        "beta0 = 1.0; beta1 = 2.0; beta2 = -3.0; beta3 = 0.4;\n",
-        "omega0 = 0.1; omega1 = -0.4; omega2 = 2.0; omega3 = 3.0;\n",
+        "beta0 = 1.0; beta1 = 2.0; beta2 = -3.0; beta3 = 0.4\n",
+        "omega0 = 0.1; omega1 = -0.4; omega2 = 2.0; omega3 = 3.0\n",
         "x = 2.3; y =2.0\n",
         "l_i_func = likelihood(x,y,beta0,beta1,beta2,beta3,omega0,omega1,omega2,omega3)\n",
         "print('l_i=%3.3f'%l_i_func)"