Project02 Recognizing Handwritten Digits.ipynb

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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# imports for array-handling and plotting\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "matplotlib.use('agg')\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# let's keep our keras backend tensorflow quiet\n",
    "import os\n",
    "os.environ['TF_CPP_MIN_LOG_LEVEL']='3'\n",
    "# for testing on CPU\n",
    "#os.environ['CUDA_VISIBLE_DEVICES'] = ''\n",
    "\n",
    "# keras imports for the dataset and building our neural network\n",
    "from keras.datasets import mnist\n",
    "from keras.models import Sequential, load_model\n",
    "from keras.layers.core import Dense, Dropout, Activation\n",
    "from keras.utils import np_utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "(X_train, y_train), (X_test, y_test) = mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 9 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "for i in range(9):\n",
    "  plt.subplot(3,3,i+1)\n",
    "  plt.tight_layout()\n",
    "  plt.imshow(X_train[i], cmap='gray_r', interpolation='none')\n",
    "  plt.title(\"Digit: {}\".format(y_train[i]))\n",
    "  plt.xticks([])\n",
    "  plt.yticks([])\n",
    "fig\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "fig = plt.figure()\n",
    "plt.subplot(2,1,1)\n",
    "plt.imshow(X_train[0], cmap='gray', interpolation='none')\n",
    "plt.title(\"Digit: {}\".format(y_train[0]))\n",
    "plt.xticks([])\n",
    "plt.yticks([])\n",
    "plt.subplot(2,1,2)\n",
    "plt.hist(X_train[0].reshape(784))\n",
    "plt.title(\"Pixel Value Distribution\")\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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