{"cells":[{"cell_type":"markdown","metadata":{"_cell_guid":"157fa8ee-5914-7f7a-fbd2-cb5b0e44ff1a"},"source":"### Load data"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"c28982fe-992b-8e32-2051-4655daaeec25"},"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)\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."},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"4d3764e0-cffd-fb6c-4884-c77a9d37506d"},"outputs":[],"source":"from keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation, Flatten\n\nimport numpy as np\nnp.random.seed(20170317)  # for reproducibility"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"9b963f35-60a6-faae-143a-60947bceb3cb"},"outputs":[],"source":"from keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Activation, Flatten"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"11e079f8-fec5-6499-50b3-745d0d3cf996"},"outputs":[],"source":""}],"metadata":{"_change_revision":0,"_is_fork":false,"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.6.0"}},"nbformat":4,"nbformat_minor":0}