validate-installation.ipynb

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  {
   "cell_type": "code",
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   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_formats = ['svg']\n",
    "\n",
    "import matplotlib as mpl\n",
    "# print('Available templates:', plt.style.available)\n",
    "# plt.style.use('ggplot')\n",
    "# plt.style.use('seaborn-poster')\n",
    "# plt.style.use('seaborn-paper')\n",
    "\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "mpl.rcParams['font.serif'] = 'Times New Roman'\n",
    "mpl.rcParams['font.size'] = 14."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "matrix = np.random.randn(10, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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   "source": [
    "loss = [0.6953163, 0.7018882, 0.65935826, 0.598709, 0.5538328, 0.53281164, 0.5181924, 0.48255932, 0.46412385, 0.453432, 0.4501256, 0.39450473, 0.40908659, 0.3833662, 0.39917272, 0.39518774, 0.40481097, 0.36237028, 0.4041135, 0.387112, 0.35119292, 0.35331517, 0.35375655, 0.36131442, 0.31293228, 0.30657303, 0.32593542, 0.35628563, 0.29453227, 0.30169517, 0.30329645, 0.2792983, 0.27637938, 0.29713252, 0.29341716, 0.3241131, 0.28253058, 0.27349338, 0.3075035, 0.28300005, 0.32466015, 0.26316854, 0.28315973, 0.27379614, 0.21708909, 0.27900043, 0.27947253, 0.30228493, 0.25622085, 0.2555356, 0.17347145, 0.32434052, 0.22184843, 0.24922094, 0.3029908, 0.194706, 0.20774634, 0.256444, 0.26532218, 0.27812994, 0.2107029, 0.22950074, 0.2074106, 0.28764537, 0.21736456, 0.22543786, 0.23822728, 0.17916393, 0.20422933, 0.24624233, 0.24323758, 0.21235587, 0.20395972, 0.24433374, 0.2032073, 0.26925242, 0.19331583, 0.24644452, 0.18844484, 0.22129892, 0.21031664, 0.1625934, 0.20031482, 0.20809731, 0.21158019, 0.20185809, 0.24271974, 0.20195979, 0.22969052, 0.23131177, 0.21388403, 0.19342108, 0.17292757, 0.17936996, 0.1852277, 0.16341394, 0.19159803, 0.1669898, 0.18459256, 0.1750191]\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(loss)\n",
    "plt.xlabel('Epochs')\n",
    "plt.ylabel('Loss')\n",
    "plt.tight_layout()\n",
    "plt.show()"
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