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jeetaf/bcan.py

Last active June 29, 2021 11:25
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bcan.py
epochs = 50
model = Sequential()
model.add(Conv1D(filters=32, kernel_size=2, activation='relu', input_shape = (30,1)))
model.add(BatchNormalization())
model.add(Dropout(0.2))
model.add(Conv1D(filters=64, kernel_size=2, activation='relu'))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Flatten())
model.add(Dense(64, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))
model.summary()
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