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📝 Update notebooks
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‎notebooks/RetailHero.ipynb‎

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‎notebooks/RetailHero_EN.ipynb‎

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‎notebooks/pipeline_usage_EN.ipynb‎

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"execution_count": 1,
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"metadata": {
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{
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"data": {
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"('./content/Hilstorm.csv', <http.client.HTTPMessage at 0x117de0438>)"
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"metadata": {},
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"outputs": [],
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"source": [
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"import urllib.request\n",
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"import pandas as pd\n",
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"\n",
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"\n",
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"csv_path = '/content/Hilstorm.csv'\n",
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"csv_path = './content/Hilstorm.csv'\n",
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"url = 'http://www.minethatdata.com/Kevin_Hillstrom_MineThatData_E-MailAnalytics_DataMiningChallenge_2008.03.20.csv'\n",
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"urllib.request.urlretrieve(url, csv_path)"
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"/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/sklearn/pipeline.py:354: UserWarning: It is recommended to use this approach on treatment balanced data. Current sample size is unbalanced.\n",
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"/Users/Maksim/Library/Python/3.6/lib/python/site-packages/sklearn/pipeline.py:354: UserWarning: It is recommended to use this approach on treatment balanced data. Current sample size is unbalanced.\n",
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" self._final_estimator.fit(Xt, y, **fit_params)\n"
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‎notebooks/pipeline_usage_RU.ipynb‎

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"('./content/Hilstorm.csv', <http.client.HTTPMessage at 0x117ee04a8>)"
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"outputs": [],
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"import urllib.request\n",
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"csv_path = '/content/Hilstorm.csv'\n",
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"csv_path = './content/Hilstorm.csv'\n",
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"url = 'http://www.minethatdata.com/Kevin_Hillstrom_MineThatData_E-MailAnalytics_DataMiningChallenge_2008.03.20.csv'\n",
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"urllib.request.urlretrieve(url, csv_path)"
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}
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"import pandas as pd\n",
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"/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/sklearn/pipeline.py:354: UserWarning: It is recommended to use this approach on treatment balanced data. Current sample size is unbalanced.\n",
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"/Users/Maksim/Library/Python/3.6/lib/python/site-packages/sklearn/pipeline.py:354: UserWarning: It is recommended to use this approach on treatment balanced data. Current sample size is unbalanced.\n",
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" self._final_estimator.fit(Xt, y, **fit_params)\n"
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"outputs": [

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