from numpy import loadtxt
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
dataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')
x = dataset[:-50,0:8]
y = dataset[:-50,8]
x_test = dataset[-50:,0:8]
y_test = dataset[-50:,8]

model = Sequential()
model.add(Dense(12, input_shape=(8,), activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
model.fit(x, y, epochs=150, batch_size=10)
_, accuracy = model.evaluate(x_test, y_test)
print('Accuracy: %.2f' % (accuracy*100))