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
Many large enterprises have established comprehensive Business Intelligence (BI) Reporting mechanisms to track Key Performance Indicators…
Personalization has become a game-changer in retail, and brands strive to give their customers customized experiences….
