Synthetic data is generated through means other than those which the target task is focused on, e.g. to be used in low resource environments.
Synthetic data generation is useful to increase the size of the dataset or change the topical focus of the training data.
Example: Robot solving Rubik’s cube – the model may first be trained on a Rubik’s cube computer simulation which is then transferred to an actual robot hand and its controls
- Keywords: machine-learning, nlp
- Source: How to Make Synthetic Data | Synthetic Data Generation for Machine Learning - YouTube