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Update 2_7_Model_Persistence.ipynb
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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""
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""
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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",
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"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",
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"\n",
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"First we recap the previous tasks: load data, preprocess and train the model."
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"First, we recap the previous tasks: load data, preprocess, and train the model."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"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."
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"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."
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]
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},
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{
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"metadata": {},
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"source": [
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"## Licence\n",
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"The notebook is freely licensed under under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
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"The notebook is freely licensed under the [Creative Commons Attribution Share-Alike license](https://creativecommons.org/licenses/by/2.0/). \n",
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"\n",
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"© Carlos A. Iglesias, Universidad Politécnica de Madrid."
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]
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