Machine Learning Hero

3.6 Data Augmentation for Image and Text Data

Data augmentation is a powerful technique that involves creating new training examples from existing data by applying various transformations. This method is widely utilized in deep learning, particularly for tasks involving images and text, to artificially expand the size of the training dataset. By doing so, data augmentation helps improve model generalization, reduce overfitting, and enhance overall performance on unseen data.

In this section, we will delve into the application of data augmentation techniques for both image data and text data, two fundamental domains in machine learning. For image data, we will explore a range of augmentation methods such as rotation, flipping, scaling, and color ...