nn.py

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import add, Dense, Dropout
from tensorflow.keras.optimizers import Adam


model = Sequential()

model.add(Dense(64,input_dim=29,activation='relu'))
model.add(Dense(32, activation = 'relu'))
model.add(Dropout(0.5))
model.add(Dense(16,activation = 'relu'))
model.add(Dropout(0.15))
model.add(Dense(1, activation = 'sigmoid'))

opt = Adam(learning_rate=1e-4, decay=1e-6)

model.compile(loss="binary_crossentropy",optimizer=opt,metrics=['Precision','Recall'])

model.fit(X_train, y_train, epochs = 5,\
                    validation_data = (X_test, y_test))