{"cells":[{"metadata":{"collapsed":true,"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","trusted":false},"cell_type":"code","source":"import pandas as pd\nimport missingno as msn\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.preprocessing import RobustScaler, MinMaxScaler\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.model_selection import cross_validate, train_test_split\nfrom sklearn.metrics import accuracy_score, classification_report, confusion_matrix\nimport tensorflow as tf\nfrom keras.models import Sequential\nfrom keras.layers import Dense\nfrom keras.layers import Dropout\n\ndata = pd.read_csv('../input/train.csv', nrows=2000000)\ndata.head()\nnew_data = data.dropna(axis = 1)\nx = new_data.drop(['is_attributed', 'click_time'], axis = 1)\nprint (x.head())\ny = new_data['is_attributed']\nprint (y.head())\nX_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.33, random_state=101)\nscaler = MinMaxScaler()\nscaled_x_train = scaler.fit_transform(X_train)\nscaled_x_test = scaler.transform(X_test)\nmodel_1 = Sequential()\nmodel_1.add(Dropout(0.2, input_shape=(5,)))\nmodel_1.add(Dense(256, activation='relu'))\nmodel_1.add(Dropout(0.2))\nmodel_1.add(Dense(128, activation='relu'))\nmodel_1.add(Dropout(0.2))\nmodel_1.add(Dense(64, activation='relu'))\nmodel_1.add(Dropout(0.2))\nmodel_1.add(Dense(32, activation='relu'))\nmodel_1.add(Dropout(0.2))\nmodel_1.add(Dense(units = 1, activation='sigmoid'))\nmodel_1.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics=['accuracy'])\nmodel_1.fit(scaled_x_train, y_train, epochs=5, validation_data=(scaled_x_test, y_test), verbose = 2)","execution_count":null,"outputs":[]},{"metadata":{"collapsed":true,"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":false},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"language_info":{"name":"python","version":"3.6.5","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"nbformat":4,"nbformat_minor":1}