Custom Callbacks

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Create custom callbacks to execute functions during training at specific events like the end of each epoch.pythonCopy codefrom tensorflow.keras.callbacks import Callback class CustomCallback(Callback): def on_epoch_end(self, epoch, logs=None): print(f"End of epoch {epoch}. Validation Loss: {logs['val_loss']}") model.fit(X_train, y_train, epochs=10, validation_data=(X_val, y_val), callbacks=[CustomCallback()])
This is useful for tracking custom metrics or making decisions during training.

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