Chapter 8 of Volume 41 covers engineering and deployment for human-in-the-loop learning pipelines

A new chapter in the STATERA Library's Volume 41 on Human-in-the-Loop Learning addresses engineering and deployment. It describes how data pipelines link raw data, human annotation, model training, and production feedback into a continuous learning process. The chapter stresses maintaining data quality, traceability, reproducibility, and operational efficiency across the model lifecycle. It outlines ingestion, schema validation, preprocessing, and human annotation stages, including quarantining invalid records and logging annotator details for auditing. It also introduces active learning as a way to prioritize informative samples and reduce labeling costs.