Data Augmentation

In the context of Artificial Intelligence (AI), Data Augmentation refers to the process of generating additional data samples from existing ones. It is a common technique used in machine learning to increase the size and diversity of the training dataset, in order to improve the performance of the models, especially when the original dataset is small or lacks diversity. Pixis uses data augmentation to train its codeless AI infrastructure and to refine the performance of its AI models to produce better results for the users.