Augmenting ML Datasets with Gretel and Vertex AI

This blog demonstrates how to utilize Gretel, an AI-based platform, in conjunction with Google Cloud Platform's (GCP) Vertex AI to create high-quality synthetic tabular data for training a classification model. The partnership between Gretel and GCP aims to accelerate MLOps by enabling the use of synthetic data to augment or replace ML training data. By using Gretel, users can increase the number of training samples and balance their datasets, thus eliminating bias in the data. This tutorial uses Gretel Cloud for easy setup and familiarization with its capabilities, but also offers options for customers to deploy their own Data Plane, known as a Gretel Hybrid Deployment, which allows all data processing to happen within their own GCP account by way of Google Kubernetes Engine (GKE).