General description of the Transformers section

Standard practice when working with training datasets is to augment an existing dataset using various transformations.

Examples:

• For images: translations, turns, reflections, distortions, noise, and more.

• For audio: processing through the equalizer and more.

Transformers allow these transformations to be done on the fly in the learning process, and not in advance when forming a training sample.