Data Augmentation involves artificially diversifying training data by applying multiple modifications, such as rotation, cropping, or noise addition, to generate new instances. As a result, the dataset is improved, and machine learning models’ capacity to generalize is enhanced.
Data Augmentation
SHARE
Related Links
AI-based credit scoring is revolutionizing the financial industry by providing more accurate, efficient, and inclusive credit…
The pandemic accelerated the decline in print newspaper circulation and news consumption across digital platforms. The…
