Data Augmentation

Data augmentation refers to the increase of data volume through various modification techniques, expanding the number of samples in the original dataset. It not only helps in growing the dataset but also enhances its diversity. During the training of machine learning models, data augmentation serves as a regularization technique, helping to prevent overfitting. Data augmentation techniques are widely used in fields such as natural language processing and computer vision, significantly improving the generalization and robustness of models.