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Clean up the beginning of the notebook

main
Aurélien Geron 2021-10-20 18:39:09 +13:00
parent d225aff822
commit 519b3529d3
1 changed files with 37 additions and 6 deletions
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43
01_the_machine_learning_landscape.ipynb
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@ -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",