TensorFlow 面试题与答案
Question: Explain the concept of data augmentation in image classification using TensorFlow.Answer: Data augmentation involves applying random transformations to input data during training to increase the diversity of the dataset. In image classification, this can include rotations, flips, and zooms.Example: data_augmentation = tf.keras.Sequential([ tf.keras.layers.experimental.preprocessing.RandomFlip('horizontal'), tf.keras.layers.experimental.preprocessing.RandomRotation(0.2), ]) |
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