Machine Learning
Machine Learning Accuracy Using Synthetic Data
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.
Read more...Transforms and Synthetics on Relational Databases
A walkthrough of our new multi-table transform and multi-table synthetics notebooks, which can be used independently or simultaneously.
Read more...Test Data Generation: Uses, Benefits, and Tips
Test data generation is the process of creating new data that replicates an original dataset. Here’s how developers and data engineers use it.
Read more...What Is Data Simulation?
Data simulation is the process of using large quantities of data to predict events and validate models. Get the full data simulation definition.
Read more...Teaching large language models to zip their lips with RLPF
Gretel introduces Reinforcement Learning from Privacy Feedback (RLPF), a novel approach to reduce the likelihood of a language model leaking private information.
Read more...How to Generate Synthetic Data: Tools and Techniques to Create Interchangeable Datasets
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.
Read more...AWS + Gretel Synthetic Data Accelerator Program for Generative AI
How our new Synthetic Data Accelerator Program with AWS will help enterprises scale responsible AI systems fast.
Read more...Introducing Gretel MLOps
Use Gretel's synthetic data platform to replace, augment, or balance training datasets within MLOps pipelines like Vertex AI, Azure ML, and Amazon SageMaker.
Read more...Synthetic Time Series Data Creation for Finance
How we generated high-quality synthetic time-series data for one of the largest financial institutions in the world.
Read more...Advanced Data Privacy: Gretel Privacy Filters and ML Accuracy
A look at how using Gretel’s Privacy Filters to immunize synthetic datasets against adversarial attacks can impact machine learning accuracy.
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