What are some of the effective data augmentation techniques for non-image data?
Trying to do semi-supervised learning on non-image data with MixMatch and FixMatch like techniques, which all require multiple ways to do data augmentation. For tabular data which columns are not meaningful (like embeddings) is there any other way to augment other than adding gaussian noise?