Gretel Blog

Use Gretel Synthetics and Colaboratory’s free GPUs to train a model to automatically generate fake, anonymized data with differential privacy guarantees.

Learn more about how Gretel's REST APIs automatically build a metastore that makes it easy to understand what is inside of your data.

We’re going to train and build our synthetic dataset off of a real-time public feed of e-bike ride-share data called the GBFS (General Bike-share Feed)

At Gretel, we realized that we can apply machine learning, synthetic data, and formal reasoning to offer provable privacy guarantees for data.

Take a deep dive on training Gretel’s open-source, synthetic data library to generate electronic health records that protect individual privacy (PII).

Look at how FastText word embeddings can help to quickly understand new datasets, and build more consistent labels for your own data.

Learn about new features in Gretel, and how those features enabled us to discover personally identifiable information (PII) in a popular Kaggle dataset.