Refactor code for improved readability and consistency across multiple Jupyter notebooks

- Added missing commas in various print statements and function calls for better syntax.
- Reformatted code to enhance clarity, including breaking long lines and aligning parameters.
- Updated function signatures to use float type for sigma parameters instead of int for better precision.
- Cleaned up comments and documentation strings for clarity and consistency.
- Ensured consistent formatting in plotting functions and data handling.

M1/Statistical Learning/TP7_Kmeans.ipynb

@@ -543,7 +543,12 @@
     "plt.plot(X[:, 0], X[:, 1], \".b\", alpha=0.2)\n",
     "for center in kmeans1.cluster_centers_:\n",
     "    plt.plot(\n",
-    "        center[0], center[1], \".\", color=\"red\", markersize=10, label=\"Cluster center\"\n",
+    "        center[0],\n",
+    "        center[1],\n",
+    "        \".\",\n",
+    "        color=\"red\",\n",
+    "        markersize=10,\n",
+    "        label=\"Cluster center\",\n",
     "    )\n",
     "plt.legend()\n",
     "plt.show()"
@@ -623,7 +628,12 @@
     "\n",
     "for center in kmeans1.cluster_centers_:\n",
     "    plt.plot(\n",
-    "        center[0], center[1], \".\", color=\"red\", markersize=10, label=\"Cluster center\"\n",
+    "        center[0],\n",
+    "        center[1],\n",
+    "        \".\",\n",
+    "        color=\"red\",\n",
+    "        markersize=10,\n",
+    "        label=\"Cluster center\",\n",
     "    )\n",
     "plt.legend()\n",
     "plt.show()"
@@ -1529,9 +1539,10 @@
     }
    ],
    "source": [
-    "import tensorflow as tf\n",
     "from scipy.stats import mode\n",
     "\n",
+    "import tensorflow as tf\n",
+    "\n",
     "mnist = tf.keras.datasets.mnist\n",
     "(X_train, y_train), (X_test, y_test) = mnist.load_data()\n",
     "\n",
@@ -1543,7 +1554,7 @@
     "\n",
     "def map_clusters_to_labels(clusters, true_labels):\n",
     "    return np.array(\n",
-    "        [mode(true_labels[clusters == i], keepdims=True).mode[0] for i in range(10)]\n",
+    "        [mode(true_labels[clusters == i], keepdims=True).mode[0] for i in range(10)],\n",
     "    )\n",
     "\n",
     "\n",