Clean up the beginning of the notebook

01_the_machine_learning_landscape.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "**Chapter 1 – The Machine Learning landscape**\n",
     "\n",
-    "_This contains the code example in this chapter 1, as well as all the code used to generate `lifesat.csv` and some of this chapter's figures._\n",
+    "_This notebook contains the code examples in chapter 1, as well as all the code used to generate `lifesat.csv` from the original data sources, and some of this chapter's figures._\n",
     "\n",
     "You're welcome to go through it if you want, but it's just a teaser: the real action starts in the next chapter."
    ]
@@ -32,6 +32,13 @@
     "# Setup"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Python 3.8 is required:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -42,11 +49,17 @@
    },
    "outputs": [],
    "source": [
-    "# Python ≥3.8 is required\n",
     "import sys\n",
     "assert sys.version_info >= (3, 8)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Make this notebook's output stable across runs:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 2,
@@ -55,28 +68,40 @@
    "source": [
     "import numpy as np\n",
     "\n",
-    "# Make this notebook's output stable across runs\n",
     "np.random.seed(42)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Scikit-Learn ≥1.0 is required:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Scikit-Learn ≥1.0 is required\n",
     "import sklearn\n",
+    "\n",
     "assert sklearn.__version__ >= \"1.0\""
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To plot pretty figures directly within Jupyter:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# To plot pretty figures directly within Jupyter\n",
     "%matplotlib inline\n",
     "import matplotlib as mpl\n",
     "\n",
@@ -84,13 +109,19 @@
     "mpl.rc('axes', labelsize=14)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Download `lifesat.csv` from github, unless it's already available locally:"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Download the data\n",
     "from pathlib import Path\n",
     "import urllib.request\n",
     "\n",