{"cells":[
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load in \n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib.pyplot as plt\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nfrom subprocess import check_output\nprint(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\n\n# Any results you write to the current directory are saved as output.\n\ntrainData = pd.read_csv(\"../input/train.csv\")\ntestData = pd.read_csv(\"../input/test.csv\")\n"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "def getLabelAndImageFromRow(row):\n    return row[0], np.reshape(row[1:], (28, 28))\n\ndef drawData(row):\n    label, image = getLabelAndImageFromRow(row)\n    plt.axis('off')\n    plt.imshow(image, cmap=plt.cm.gray_r, interpolation='nearest')\n    plt.title('Training: %i' % label)\n    \ndef drawDataList(dataList):\n    ITEMS_EACH_ROW = 4\n    size = len(dataList)\n    num_of_row = np.ceil(float(size)/ITEMS_EACH_ROW)\n    \n    for index, row in enumerate(dataList):\n        plt.subplot(num_of_row, ITEMS_EACH_ROW, index + 1)\n        drawData(row)\n        \ndrawDataList(trainData.values[:8])"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "from sklearn.svm import SVC\nclf = SVC(gamma=0.001)\nclf.fit(trainData.values[:100, 1:], trainData.values[:100, 0])"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": ""
 }
],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}}, "nbformat": 4, "nbformat_minor": 0}