Data science

Synthetic data is artificially annotated information that is generated by computer algorithms or simulations, commonly used as an alternative to real-world data.

Beta2 for Gretel.ai is all about delivering privacy engineering as a service through clean, simple APIs.

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

How Gretel's data quality analysis tools for evaluating generated text can help you optimize the performance LLMs, like the Llama-2 model.

Can synthetic data really be used in machine learning? We explore the utility of synthetic data created from popular datasets and tested on popular ML algorithms.

Everything you need to know about anonymizing data and the techniques for mitigating privacy risks.

Announcing the open beta release of our DGAN model type.

Quickly and safely aggregate geolocation data for location density analysis using a hexagonal grid system.

How combining agent-based methods, LLMs, and synthetic data enables natural language queries for databases and data warehouses, sans SQL.

Let’s fine tune and prompt a large language model to swap the sentiment of product reviews!