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افزایش داده ها
Data Augmentation 309
artificially growing the training set is called data augmentation or training set expansion.
In this section we will present some of the most popular regularization techniques for neural networks, and how to implement them with TensorFlow: early stopping, ℓ1 and ℓ2 regularization, dropout, max-norm regularization, and data augmentation.
Data Augmentation
One last regularization technique, data augmentation, consists of generating new training instances from existing ones, artificially boosting the size of the training set.
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