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briandalessandrobriandalessandro
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lecture 10/18
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‎ipython/Labs_Student/Lab_Sklearn_Magic.ipynb‎

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‎ipython/Labs_Student/Lab_Sklearn_Magic_Student.ipynb‎

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"- http://scikit-learn.org/stable/modules/preprocessing.html\n",
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"- http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.StandardScaler.html#sklearn.preprocessing.StandardScaler\n",
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"- http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html#sklearn.preprocessing.PolynomialFeatures\n",
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"- http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html#sklearn.model_selection.GridSearchCV\n",
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"- http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html\n",
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"- http://scikit-learn.org/stable/modules/pipeline.html#pipeline\n",
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"\n",
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"Also, here is a helpful tutorial that explains how to use much of the above:\n",
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"import os\n",
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"import pandas as pd\n",
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"from sklearn.linear_model import LogisticRegression\n",
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"from sklearn.grid_search import GridSearchCV\n",
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"from sklearn.cross_validation import KFold\n",
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"from sklearn.model_selection import GridSearchCV\n",
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"from sklearn.model_selection import KFold\n",
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline\n",
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"\n",
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "Python [py35]",
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"display_name": "Python 3",
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"language": "python",
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"name": "Python [py35]"
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {

‎ipython/python35/Lecture_Binning_NonLinear_3.ipynb‎

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‎ipython/python35/Lecture_FeatureSelection_3.ipynb‎

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‎ipython/python35/Lecture_Regularization_3.ipynb‎

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