Load data matrix using Numpy

load.ipynb

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   "source": [
    "import numpy as np"
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    {
     "data": {
      "text/plain": [
       "array([[ 1.1444092e-05, -6.1035156e-05,  8.0108643e-05, ...,\n",
       "        -7.8201294e-05,  1.9073486e-05,  1.1444092e-05],\n",
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       "       [ 1.1444092e-05, -6.1035156e-05,  8.0108643e-05, ...,\n",
       "        -7.8201294e-05,  1.9073486e-05,  1.1444092e-05],\n",
       "       ...,\n",
       "       [ 2.4229137e+01,  2.3110016e+01,  2.1340733e+01, ...,\n",
       "        -9.5795441e-01, -7.3286438e-01, -4.2309189e-01],\n",
       "       [ 2.4168774e+01,  2.2969147e+01,  2.1114292e+01, ...,\n",
       "         1.0905056e+00,  1.1677818e+00,  1.3992653e+00],\n",
       "       [ 2.9535503e+01,  2.7498508e+01,  2.4384159e+01, ...,\n",
       "         4.9166622e+00,  3.2706280e+00,  1.2978973e+00]], dtype=float32)"
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     "execution_count": 5,
     "metadata": {},
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   "source": [
    "np.load(\"teste.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.1444092e-05 -6.1035156e-05  8.0108643e-05 -6.1035156e-05\n",
      "  2.2888184e-05 -2.6702881e-05 -5.3405762e-05 -4.5776367e-05\n",
      " -2.2888184e-05 -2.6702881e-05 -3.0517578e-05 -3.8146973e-05\n",
      "  9.9182129e-05  4.1961670e-05  0.0000000e+00 -5.7220459e-05\n",
      " -7.8201294e-05  1.9073486e-05  1.1444092e-05]\n"
     ]
    }
   ],
   "source": [
    "with open(\"teste.npy\", \"rb\") as f:\n",
    "    data = np.load(f)\n",
    "    print(data[0])"
   ]
  }
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