What are advanced callbacks in TensorFlow Keras?

What are advanced callbacks in TensorFlow Keras?

Advanced callbacks in TensorFlow Keras are tools that allow you to customize the training process, such as saving models, adjusting learning rates, or stopping training early based on certain conditions.

Can you give me an example of how to implement a custom callback?

Sure! You can create a custom callback by subclassing tf.keras.callbacks.Callback and overriding methods like on_epoch_end or on_batch_end to define your custom behavior.

What are some built-in callbacks I can use?

Some built-in callbacks include ModelCheckpoint, EarlyStopping, and ReduceLROnPlateau, which help manage model training effectively.

How do I use the EarlyStopping callback?

You can use the EarlyStopping callback by specifying parameters like monitor, patience, and restore_best_weights when you instantiate it, then pass it to the fit method.