Synthetic Data Metrics is an open-source Python library for evaluating model-agnostic tabular data by pitching machine generated data sets against real data sets.
It seems like every passing month brings more hype to the field of synthetic data - and more AI startups and open source projects. But how far have we come? Some plausible use cases are emerging, but has synthetic data really addressed its limitations?