Data Augmentation
Data augmentation is the practice of artificially expanding a training dataset by applying transformations to existing examples — such as rotating images or paraphrasing text — so a model sees more variation without needing to collect new labeled data.
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Glossary Terms(3)
Synthetic Data
Synthetic data is artificially generated data — produced by algorithms, simulations, or generative models rather than collected from real-world events — that i…
Data Augmentation
Data augmentation is the practice of artificially expanding a training dataset by applying transformations to existing examples — such as rotating images or pa…
Feature Engineering
Feature engineering is the process of using domain knowledge to select, transform, and create the input variables (features) that a machine learning model is t…