{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"f3290d35-aa8f-7c49-203c-8c3abaab9f3e"},"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":"5e866d6c-29e7-9318-4058-553856da3804"},"outputs":[],"source":"import keras"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"191c35b6-093e-3e4b-75e6-cb3e5a09cd30"},"outputs":[],"source":"import theano"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"76706db0-680f-25e7-a4a0-77c73dc9237c"},"outputs":[],"source":"import mxnet"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"5a16f07d-1f38-0a1e-c6f5-003a5cc19122"},"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}