Open Source

Assessing the efficacy and quality of synthetic data with Gretel Evaluate API.

In this post, we walk through building a data pipeline that will automatically transform datasets so they can be safely used in development environments.

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

In this blog, we will use Fluent Bit to collect logs from AWS EKS cluster applications.

Our new configuration templates will help you pick some of the right parameters needed to train your synthetic data models.

Generate artificial records to balance biased datasets and improve overall model accuracy.

We explore the popular open-source package Optuna to demonstrate how you can optimize your model hyperparameters and build the best synthetic model possible.

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

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

How to train a FastCUT GAN on public location data from a few cities to predict realistic e-bike locations across the world.