The What, Why and How of MLOps on AWS

The What, Why and How of MLOps on AWS

MLOps, a close relative to DevOps, is a combination of philosophies and practices designed to enable data science and IT teams to rapidly develop, deploy, maintain, and scale out Machine Learning models. In this session, explore the features in Amazon SageMaker Pipelines that help you increase automation, track data lineage, catalog ML models for production, improve the quality of your end-to-end workflows, and support governance. Also, learn how to use SageMaker projects, which provide MLOps templates for incorporating CI/CD practices into your ML pipelines.