imports after title

Author: mdeff

notebooks/02_spectral.ipynb

@@ -1,5 +1,16 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 2 Spectral Graph Theory\n",
+    "\n",
+    "We'll see here two of the most celebrated algorithms stemming from Spectral Graph Theory:\n",
+    "1. [Spectral clustering](https://en.wikipedia.org/wiki/Spectral_clustering): clustering data using a similarity graphs\n",
+    "1. [Laplacian eigenmaps](https://en.wikipedia.org/wiki/Nonlinear_dimensionality_reduction#Laplacian_eigenmaps): dimensionality reduction which preserves geodesic distances"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -18,17 +29,6 @@
     "from mpl_toolkits.mplot3d import Axes3D"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# 2 Spectral Graph Theory\n",
-    "\n",
-    "We'll see here two of the most celebrated algorithms stemming from Spectral Graph Theory:\n",
-    "1. [Spectral clustering](https://en.wikipedia.org/wiki/Spectral_clustering): clustering data using a similarity graphs\n",
-    "1. [Laplacian eigenmaps](https://en.wikipedia.org/wiki/Nonlinear_dimensionality_reduction#Laplacian_eigenmaps): dimensionality reduction which preserves geodesic distances"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},