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Update 2_7_Model_Persistence.ipynb

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Carlos A. Iglesias 2025-06-02 17:17:43 +03:00 committed by GitHub
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ml1/2_7_Model_Persistence.ipynb
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@ -4,7 +4,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"![](files/images/EscUpmPolit_p.gif \"UPM\")" "![](./images/EscUpmPolit_p.gif \"UPM\")"
] ]
}, },
{ {
@ -48,9 +48,9 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"The goal of this notebook is to learn how to save a model in the the scikit by using Python’s built-in persistence model, namely pickle\n", "The goal of this notebook is to learn how to save a model in the scikit by using Python’s built-in persistence model, namely pickle\n",
"\n", "\n",
"First we recap the previous tasks: load data, preprocess and train the model." "First, we recap the previous tasks: load data, preprocess, and train the model."
] ]
}, },
{ {
@ -107,7 +107,7 @@
"cell_type": "markdown", "cell_type": "markdown",
"metadata": {}, "metadata": {},
"source": [ "source": [
"A more efficient alternative to pickle is joblib, especially for big data problems. In this case the model can only be saved to a file and not to a string." "A more efficient alternative to pickle is joblib, especially for big data problems. In this case, the model can only be saved to a file and not to a string."
] ]
}, },
{ {
@ -146,7 +146,7 @@
"metadata": {}, "metadata": {},
"source": [ "source": [
"## Licence\n", "## Licence\n",
"The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n", "The notebook is freely licensed under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
"\n", "\n",
"© Carlos A. Iglesias, Universidad Politécnica de Madrid." "© Carlos A. Iglesias, Universidad Politécnica de Madrid."
] ]