corrected notebook front matter

Author: hamelsmu

_notebooks/book_equations.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Equations\n",
+    "> Supplementary material on Equations\n",
+    "\n",
     "- permalink: /book_equations\n",
     "\n",
     "*This notebook lists all the equations in the book. If you decide to print them on a T-Shirt, I definitely want a copy! ;-)*\n",

_notebooks/extra_gradient_descent_comparison.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Comparison of Batch, Mini-Batch and Stochastic Gradient Descent\n",
+    "> Supplementary material on Gradient Descent\n",
+    "\n",
     "- permalink: /extra_gradient_descent_comparison"
    ]
   },

_notebooks/math_linear_algebra.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Math - Linear Algebra\n",
+    "> Supplementary material on Linear Algebra\n",
+    "\n",
     "- permalink: /math_linear_algebra\n",
     "\n",
     "*Linear Algebra is the branch of mathematics that studies [vector spaces](https://en.wikipedia.org/wiki/Vector_space) and linear transformations between vector spaces, such as rotating a shape, scaling it up or down, translating it (ie. moving it), etc.*\n",

_notebooks/tools_matplotlib.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Tools - matplotlib\n",
+    "> Supplementary material on matplotlib\n",
+    "\n",
     "- permalink: /tools_matplotlib\n",
     "\n",
     "*This notebook demonstrates how to use the matplotlib library to plot beautiful graphs.*"

_notebooks/tools_numpy.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Tools - NumPy\n",
+    "> Supplementary material on numpy\n",
+    "\n",
     "- permalink: /tools_numpy\n",
     "\n",
     "*NumPy is the fundamental library for scientific computing with Python. NumPy is centered around a powerful N-dimensional array object, and it also contains useful linear algebra, Fourier transform, and random number functions.*\n",

_notebooks/tools_pandas.ipynb

@@ -5,6 +5,8 @@
    "metadata": {},
    "source": [
     "# Tools - pandas\n",
+    "> Supplementary material on pandas\n",
+    "\n",
     "- permalink: /tools_pandas\n",
     "\n",
     "*The `pandas` library provides high-performance, easy-to-use data structures and data analysis tools. The main data structure is the `DataFrame`, which you can think of as an in-memory 2D table (like a spreadsheet, with column names and row labels). Many features available in Excel are available programmatically, such as creating pivot tables, computing columns based on other columns, plotting graphs, etc. You can also group rows by column value, or join tables much like in SQL. Pandas is also great at handling time series.*\n",