Data labeling pipeline

Automate and streamline the annotation of raw data for machine learning model training.

A data labeling pipeline is a structured workflow for efficiently and accurately annotating large datasets. It integrates various tools and processes (e.g., human annotators, active learning, programmatic labeling) to transform raw data (images, text, audio) into labeled examples for supervised machine learning. This pipeline ensures data quality, reduces manual effort, and accelerates model development cycles, directly impacting the performance of AI applications like computer vision and natural language processing.

https://www.ibm.com/cloud/architecture/architectures/data-labeling-pipeline