diff --git a/01a_machine_learning.ipynb b/01a_machine_learning.ipynb
index e8bff60..3df48ef 100755
--- a/01a_machine_learning.ipynb
+++ b/01a_machine_learning.ipynb
@@ -952,11 +952,11 @@
     "# Generating the x axis\n",
     "x = np.linspace(0, 1, 100)\n",
     "plots = []\n",
-    "for p in range(len(params)):\n",
-    "    poly = np.poly1d(params[p])\n",
+    "for ind, param in enumerate(params):\n",
+    "    poly = np.poly1d(param)\n",
     "    epsilon = np.random.uniform(-eps, eps, x.shape)\n",
     "    y = poly(x) + epsilon\n",
-    "    plots.append(scatter(x, y, title=\"Problem \"+(str(p+1))))"
+    "    plots.append(scatter(x, y, title=\"Problem \"+(str(ind+1))))"
    ]
   },
   {
@@ -1051,11 +1051,11 @@
     "# Generating the x axis\n",
     "x = np.linspace(0, 1, 100)\n",
     "plots = []\n",
-    "for p in range(len(noise_levels)):\n",
+    "for ind, noise_level in enumerate(noise_levels):\n",
     "    poly = np.poly1d(params)\n",
-    "    epsilon = np.random.uniform(-noise_levels[p],noise_levels[p],x.shape)\n",
+    "    epsilon = np.random.uniform(-noise_level, noise_level, x.shape)\n",
     "    y = poly(x) + epsilon\n",
-    "    plots.append(scatter(x, y, title=\"Problem \"+(str(p+1))))"
+    "    plots.append(scatter(x, y, title=\"Problem \"+(str(ind+1))))"
    ]
   },
   {
@@ -2908,4 +2908,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}
\ No newline at end of file