keras_simplest_example

gistfile1.txt

import numpy as np
from keras.models import Sequential
from keras.layers import Dense

X_train = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y_train = np.array([[0], [1], [1], [0]])

model = Sequential()
model.add(Dense(2, input_dim=2, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])

model.fit(X_train, y_train, epochs=1000, verbose=0)

X_test = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
predictions = model.predict(X_test)
print("Predictions:")
print(predictions)