{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","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\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"import tensorflow as tf\nfrom tensorflow import keras","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"945d97e12ad29a4e07c39be282225fb32785bcd0"},"cell_type":"code","source":"(train_X,train_Y),(test_X,test_Y) = tf.keras.datasets.mnist.load_data()\nques = pd.read_csv(\"../input/test.csv\")\ntrain_X = tf.keras.utils.normalize(train_X,axis=1)\ntest_X = tf.keras.utils.normalize(test_X,axis=1)\ntest = ques.values\nprint (train_X.shape,test_X.shape)\n\ntrain_X = train_X.reshape(-1,28,28,1)\ntest_X = train_X.reshape(-1,28,28,1)\ntest = test.reshape(-1,28,28,1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"fb10499b806422042d280f3ae9c0fec17379d561"},"cell_type":"code","source":"model = keras.models.Sequential()\nmodel.add(keras.layers.Conv2D(filters=32,kernel_size=(5,5),activation=tf.nn.relu,padding='SAME'))\n\nmodel.add(keras.layers.Conv2D(filters=64,kernel_size=(5,5),activation='relu',padding=\"SAME\"))\n#model.add(keras.layers.BatchNormalization())\nmodel.add(keras.layers.MaxPooling2D(pool_size=(3,3)))\nmodel.add(keras.layers.Dropout(0.25))\n\nmodel.add(keras.layers.Conv2D(filters=32,kernel_size=(3,3),activation='relu',padding=\"SAME\"))\n#model.add(keras.layers.BatchNormalization())\nmodel.add(keras.layers.MaxPooling2D(pool_size=(2,2),strides=(2,2)))\nmodel.add(keras.layers.Dropout(0.5))\n\nmodel.add(keras.layers.Conv2D(filters=64,kernel_size=(3,3),activation='relu',padding=\"SAME\"))\nmodel.add(keras.layers.MaxPooling2D(pool_size=(3,3),strides=(2,2)))\nmodel.add(keras.layers.Dropout(0.5))\n\n\n\nmodel.add(keras.layers.Flatten())\n\nmodel.add(keras.layers.Dense(128,activation='relu'))\nmodel.add(keras.layers.Dense(256,activation='relu'))\nmodel.add(keras.layers.Dense(128,activation='relu'))\nmodel.add(keras.layers.Dense(10,activation='softmax'))\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"9886d5a6c3a28d15981c2c208ceae10d5b8b59ee"},"cell_type":"code","source":"\nmodel.compile(metrics=['accuracy'],loss='sparse_categorical_crossentropy',optimizer='adam')\nmodel.fit(train_X,train_Y,epochs=15)\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"68e539477caa19f248a9df365231531db9d0df18"},"cell_type":"code","source":"print (model.evaluate(test_X,test_Y))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"24d38ec201102a37066baa9a02c8c0451205ae6a"},"cell_type":"code","source":"answer = model.predict(test)\n\nf = open(\"answer.txt\",\"w\")\nf.write(\"ImageId,Label\\n\")\ni = 1\nfor j in answer:\n    f.write(str(i)+\",\"+str(np.argmax(j))+\"\\n\")\n    i += 1\nf.close()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"1f1b5d01f2d75c146ac7ef94c1eda73b2c0f8632"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}