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from keras.layers import Dense

from keras.layers import Dropout

from keras.models import Sequential

import numpy as np # linear algebra

np.array(x_train)

x_train = np.array(x_train)
x_test = np.array(x_test)
y_train = np.array(y_train)
y_test = np.array(y_test)

model = Sequential([Dense(units=16, input_dim=29, activation='relu'), Dense(units=24, activation='relu'), Dropout(0.5), Dense(20, activation='relu'), Dense(24, activation='relu'), Dense(1, activation='sigmoid')])
model.summary()

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model.fit(x_train, y_train, batch_size=15, epochs=5)