.svg){kind=icon}
.svg){kind=icon}
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
A CMO recently asked me a deceptively simple question: “If we gave an AI agent full…
I once watched a campaign manager juggle ten tools, fifteen stakeholders, and a spreadsheet that looked…
