dataaugmentasjon
Dataaugmentasjon is a Norwegian term that translates to data augmentation in English. It refers to a set of techniques used in machine learning and artificial intelligence to artificially expand the size and diversity of training datasets. The primary goal of data augmentasjon is to improve the generalization capability of models by introducing variability in the training data, thereby reducing overfitting and enhancing model robustness.
Data augmentation methods vary depending on the type of data involved. For image data, common approaches include
Implementing data augmentasjon can lead to several benefits, including improved accuracy, better handling of diverse real-world
While data augmentation offers significant advantages, it also requires careful consideration to avoid introducing unnatural or
Overall, data augmentasjon is a crucial strategy in modern machine learning workflows, facilitating the development of