TensorFlow 面试题与答案
Question: Explain the concept of model checkpoints in TensorFlow.Answer: Model checkpoints are a way to save the current state of a model during training. They can be used to resume training, fine-tune a model, or deploy a trained model.Example: checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(filepath='model_checkpoint.h5', save_best_only=True) |
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