基于surprise库和Tensorflow框架的电影推荐.ipynb

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   "source": [
    "# 数据导入与格式转换"
   ]
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   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
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     "end_time": "2019-07-10T12:14:46.065197Z",
     "start_time": "2019-07-10T12:14:37.070644Z"
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   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000209 entries, 0 to 1000208\n",
      "Data columns (total 4 columns):\n",
      "user         1000209 non-null int64\n",
      "item         1000209 non-null int64\n",
      "rate         1000209 non-null int64\n",
      "timestamp    1000209 non-null int64\n",
      "dtypes: int64(4)\n",
      "memory usage: 30.5 MB\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "col_names = ['user', 'item', 'rate', 'timestamp']\n",
    "df = pd.read_csv('./movielens/ml-1m/ratings.dat', sep = '::', header = None, names = col_names, engine = 'python')\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-10T12:15:05.099133Z",
     "start_time": "2019-07-10T12:15:04.981053Z"
    }
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   "outputs": [
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       "    user  item  rate  timestamp\n",
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   "execution_count": 23,
   "metadata": {
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     "end_time": "2019-07-10T12:15:06.006870Z",
     "start_time": "2019-07-10T12:15:05.770942Z"
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       "      <th>427702</th>\n",
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       "      <td>4</td>\n",
       "      <td>973796689</td>\n",
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       "    <tr>\n",
       "      <th>1966</th>\n",
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       "      <td>978154768</td>\n",
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       "        user  item  rate  timestamp\n",
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     "execution_count": 23,
     "metadata": {},
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   "source": [
    "df.sort_values(by = ['item']).head()"
   ]
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   "cell_type": "code",
   "execution_count": 24,
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     "end_time": "2019-07-10T12:15:06.605402Z",
     "start_time": "2019-07-10T12:15:06.563370Z"
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   },
   "outputs": [],
   "source": [
    "df['user'] -= 1\n",
    "df['item'] -= 1"
   ]
  },
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   "cell_type": "code",
   "execution_count": 25,
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    "ExecuteTime": {
     "end_time": "2019-07-10T12:15:08.435669Z",
     "start_time": "2019-07-10T12:15:08.400642Z"
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   "outputs": [],
   "source": [
    "df['rate'] = df['rate'].astype('float64')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 定义随机生成batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ShuffleDataIterator():\n",
    "    def __init__(self, inputs, batch_size = 10):\n",
    "        "
   ]
  }
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