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    "___\n",
    "___\n",
    "# Turicreate: Departure from Graphlab\n",
    "\n",
    "Turi Create simplifies the development of custom machine learning models. \n",
    "___\n",
    "___\n",
    "\n",
    "https://github.com/apple/turicreate\n"
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    "You don't have to be a machine learning expert to add\n",
    "- recommendations, \n",
    "- object detection, \n",
    "- image classification, \n",
    "- image similarity  \n",
    "- activity classification \n",
    "\n",
    "to your app.\n",
    "    \n",
    "- https://apple.github.io/turicreate/docs/userguide/\n",
    "- https://apple.github.io/turicreate/docs/api/index.html"
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    "\n",
    "# pip install -U turicreate"
   ]
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      "------------------------------------------------------\n",
      "Inferred types from first 100 line(s) of file as \n",
      "column_type_hints=[str]\n",
      "If parsing fails due to incorrect types, you can correct\n",
      "the inferred type list above and pass it to read_csv in\n",
      "the column_type_hints argument\n",
      "------------------------------------------------------\n"
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   "source": [
    "import turicreate as tc\n",
    "actions = tc.SFrame.read_csv('/Users/datalab/bigdata/cjc/ml-1m/ratings.dat', delimiter='\\n', \n",
    "                                header=False)['X1'].apply(lambda x: x.split('::')).unpack()\n",
    "for col in actions.column_names():\n",
    "    actions[col] = actions[col].astype(int)\n",
    "actions = actions.rename({'X.0': 'user_id', 'X.1': 'movie_id', 'X.2': 'rating', 'X.3': 'timestamp'})\n",
    "#actions.save('ratings')"
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