You’ve decided Machine Learning (ML) can help your customers? Great! ML is very accessible these days. But taking those ML solutions into production in a way that is repeatable, maintainable, and scalable can be challenging. MLOps draws from DevOps and Agile practices to reduce these risks and improve outcomes.
This talk is an introduction to MLOps, including: what it is, how it is similar & different from other * Ops practices, and then we’ll apply these MLOps concepts to three case studies during the session. This talk will teach attendees to recognize anti-patterns for machine learning & its deployment; and use Agile approaches to avoid these anti-patterns.