Question: How do you implement early stopping in a TensorFlow model training process?

Answer: Early stopping can be implemented using callbacks, such as tf.keras.callbacks.EarlyStopping. It monitors a specified metric and stops training if the metric does not improve after a certain number of epochs.

Example:

early_stopping = tf.keras.callbacks.EarlyStopping(monitor='val_loss', patience=3)
model.fit(train_data, epochs=100, callbacks=[early_stopping])

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