Data augmentation
Friday, April 12, 20191 min read
Data augmentation is the technique of increasing the size of data used for training a model. For reliable predictions, the deep learning models often require a lot of training data, which is not always available. Therefore, the existing data is augmented in order to make a better generalized model.
For example, in case of images, the original image can be transformed using techniques such as flipping, rotation, color jittering etc.
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Read the complete post at OpenGenus IQ, written by me as a part of GSSoC.
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