Machine Learning

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!

Set up a cutting-edge environment for deep learning with TensorFlow 2.10, PyTorch, Docker, and GPU support.

Gretel's synthetic data platform overcomes challenges across the data-centric machine learning life cycle to enable ML and AI solutions.

Learn to prepare tabular data for AI and ML with an end-to-end data cleaning workflow.

Here's how a hospital uses Gretel to help forecast staffing and resource needs for their emergency care unit, and to identify emerging trends in outbreaks.

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

Gretel GPT supports new, state-of-the-art LLMs, and makes it easier for you to trust the privacy and accuracy of LLMs for enterprise use-cases.

Data sharing is central to modern business but entails risks. Synthetic data can enable data sharing while reducing the risk of privacy-compromising linkage attacks.

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