07_regression.ipynb

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    "# IGNORE THIS CELL WHICH CUSTOMIZES LAYOUT AND STYLING OF THE NOTEBOOK !\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore', category=FutureWarning)\n",
    "warnings.filterwarnings('ignore', category=DeprecationWarning)\n",
    "warnings.filterwarnings = lambda *a, **kw: None\n",
    "from IPython.core.display import HTML; HTML(open(\"custom.html\", \"r\").read())"
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   "source": [
    "# Chapter 7: Regression\n",
    "\n",
    "Regression belongs like classification to the field of supervised learning. \n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
    "<i class=\"fa fa-info-circle\"></i>&nbsp; \n",
    "<strong>Regression predicts numerical values</strong> \n",
    "in contrast to classification which predicts categories.\n",
    "</div>\n",
    "\n",
    "<img src=\"https://i.imgflip.com/30416v.jpg\" title=\"made at imgflip.com\" width=35%/>\n",
    "\n",
    "<div class=\"alert alert-block alert-warning\">\n",
    "<i class=\"fa fa-info-circle\"></i>&nbsp; \n",
    "    Other differences are:\n",
    "\n",
    "* Accuracy is measured differently\n",
    "\n",
    "\n",
    "* Other algorithms\n",
    "</div>"
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    "## Example: Salmon weight\n",
    "\n",
    "The dataset `salmon.csv` holds measurements of `circumference`, `length` and `weight` for  `atlantic` and `sockeye` salmons.\n",
    "\n",
    "Our goal is to predict `weight` based on the other three features."
   ]
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   "cell_type": "code",
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       "<div>\n",
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       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>circumference</th>\n",
       "      <th>length</th>\n",
       "      <th>kind</th>\n",
       "      <th>weight</th>\n",