- You can define your own loss function or metrics to suit specific tasks:pythonCopy code
import tensorflow.keras.backend as K def custom_loss(y_true, y_pred): return K.mean(K.square(y_pred - y_true)) model.compile(optimizer='adam', loss=custom_loss, metrics=['accuracy'])
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