Data Augmentation

Data augmentation is like photocopying a picture, then cutting it up and reassembling it to create new versions. This helps train AI models to be more robust by exposing them to different variations of the same data. For example, if you're training a model to recognize dogs, data augmentation might involve rotating, flipping, or adding noise to pictures of dogs to create new training examples.