{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"ef1ddaf0-8d9f-b09d-a58b-766672211f83"},"outputs":[],"source":"#Dependences\nimport os\nimport numpy as np\nfrom keras.models import Sequential\nfrom keras.layers import Activation, Dropout, Flatten, Dense\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D\nfrom keras import optimizers"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"54154dbc-23ff-78cf-2457-37d143cf5b11"},"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\n#import numpy as np # linear algebra\n#import 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":"4477df7c-df67-6599-19aa-378a94bcf03a"},"outputs":[],"source":"import matplotlib.pyplot as plt"},{"cell_type":"code","execution_count":null,"metadata":{"_cell_guid":"a21a7524-eafd-b467-5445-56302a2ba728"},"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}