Gretel Blog

Data simulation is the process of using large quantities of data to predict events and validate models. Get the full data simulation definition.

An evaluation of the effect of sampling procedures on the quality of synthetic tabular data using Gretel.ai's Synthetic Quality Score (SQS).

Generate synthetic time series data with Gretel.ai’s open-source PyTorch implementation of DoppelGANger.

How we implemented a practical attack on a synthetic data model to validate its ability to protect sensitive information under different parameter settings.

Augment machine learning datasets with synthetically generated text and labels using an open-source implementation of GPT-3.

Explore state-of-the-art image synthetics for business documents using diffusion models.

A brief exploration of model soup, the new ensembling technique that takes the average weights of multiple models to improve overall performance.

Machine learning models can be trained to recognize patterns in datasets. By utilizing algorithms, they can learn to make decisions based on these patterns.

Promising evidence that state-of-the-art synthetic data models can produce artificial versions of even highly dimensional and complex genomic and phenotypic data.

Five new features that will make synthesizing data easier for busy developers and data scientists.

Use synthetic data to improve model accuracy for fraud, cyber security, or any classification task with an extremely limited minority class.

Synthetic data is algorithmically generated data that mirrors the statistical properties of the dataset it’s based on. Learn how to make high-quality synthetic data.