import tensorflow as tf
import numpy as np
x= np.array([[0,0],[0,1],[1,0],[1,1]],dtype=np.float32)
y= 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,y,epochs=1000,verbose=0)
pred=model.predict(x)
rounded_pred=np.round(pred)
print("Predictions:",rounded_pred)

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