A machine learning pipeline system with integrated training, inference, and monitoring stages for continuous model deployment and drift detection.

Patentradars sammanfattning

The invention describes a comprehensive machine learning operations (MLOps) framework comprising two primary pipelines: a training pipeline (10) with stages for data ingestion, preprocessing, model training, evaluation, registration, and deployment; and an inference pipeline (20) with corresponding data processing and model operation stages. The system includes integrated drift detection (25) and data/model monitoring (24) capabilities to maintain model performance and reliability in production environments.

AI-genererad och redaktionellt processad.