Continuous Delivery for Machine Learning (CD4ML) deals with the challenges of applying Continuous Delivery principles to ML systems to make the end-to-end process of developing and deploying them more repeatable and reliable. These systems are generally more complex than traditional software applications, and ML models are non-deterministic and hard to explain. In this talk we will discuss the challenges of testing and quality in ML systems, and share some practices for applying different types of tests to help overcome those issues.
Mini-bio: Danilo Sato is a principal consultant at ThoughtWorks with experience in many areas of architecture and engineering: software, data, infrastructure, and machine learning. He is the author of “DevOps in Practice: Reliable and Automated Software Delivery”, a member of ThoughtWorks Technology Advisory Board, and ThoughtWorks Office of the CTO.