Data augmentation involves the process of creating new data points by manipulating the original data. For example, for images, this can be done by rotating, resizing, cropping, and more.
This process increases the diversity of the data available for training models in deep learning without having to actually collect new data. This then, generally speaking, improves the performance of deep learning models.
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