Data Preprocessing Questions
Data augmentation refers to the technique of artificially increasing the size of a dataset by applying various transformations or modifications to the existing data samples. These transformations can include rotations, translations, scaling, flipping, cropping, or adding noise to the data. The purpose of data augmentation is to introduce diversity and variability into the dataset, which helps in improving the performance and generalization of machine learning models.