{"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\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 read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 5GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Data prep","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"import pandas as pd","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train = pd.read_csv('/kaggle/input/digit-recognizer/train.csv')\ntrain.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"x_train = train.drop('label', axis=1).to_numpy()\ny_train = train['label'].to_numpy()\nprint(x_train.shape, y_train.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"x_train = x_train.reshape(-1, 28, 28, 1)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Model","execution_count":null},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import tensorflow as tf","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"model = tf.keras.models.Sequential([\n    tf.keras.layers.Conv2D(16, (3,3), activation='relu', input_shape=(28,28,1)),\n    tf.keras.layers.MaxPooling2D(),\n    tf.keras.layers.Conv2D(32, (3,3), activation='relu'),\n    tf.keras.layers.MaxPooling2D(),\n    tf.keras.layers.Conv2D(64, (3,3), activation='relu'),\n    tf.keras.layers.MaxPooling2D(),\n    tf.keras.layers.Flatten(),\n    tf.keras.layers.Dense(10, activation='softmax')\n])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"model.compile(optimizer=tf.keras.optimizers.RMSprop(lr=0.001), loss='sparse_categorical_crossentropy', metrics=['accuracy'])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"history = model.fit(x_train, y_train, epochs=20, validation_split=0.2, shuffle=True)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# All training data\nhistory = model.fit(x_train, y_train, epochs=20)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Predictions","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"test = pd.read_csv('/kaggle/input/digit-recognizer/test.csv').to_numpy()\nprint(test.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"test = test.reshape(-1, 28, 28, 1)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"preds = model.predict(test)","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## Submission","execution_count":null},{"metadata":{"trusted":true},"cell_type":"code","source":"df = pd.DataFrame(np.argmax(preds, axis=1), columns=['Label'])\ndf.insert(0, 'ImageId', df.index + 1)\ndf.to_csv('submission.csv', index=False)","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}