import tensorflow as tf
import numpy as np
x_data=np.array([[0,0],[0,1],[1,0],[1,1]],dtype=np.float32)
y_data=np.array([[0],[1],[1],[0]],dtype=np.float32)
model=tf.keras.Sequential([tf.keras.layers.Dense(8,input_dim=2,activation='relu'),tf.keras.layers.Dense(8,activation='relu'),tf.keras.layers.Dense(1,activation='sigmoid')])
model.compile(optimizer='adam',loss='binary_crossentropy',metrics=['accuracy'])
model.fit(x_data,y_data,epochs=1000,verbose=0)
predictions=model.predict(x_data)
rounded_predictions=np.round(predictions)
print("Predictions:",rounded_predictions)

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