This document provides a reference architecture for building a standardized pipeline with Google Cloud and Labelbox. This architecture can help you to develop your ML models more quickly, particularly models for computer vision, NLP and generative AI use cases. This document is intended for machine learning (ML) engineers and data scientists who want to incorporate automation and a human-in-the-loop (HITL) approach to data labeling and data curation
Model development and data labeling with Google Cloud and Labelbox | Cloud Architecture Center
