You want to scale your use of AI, but you are blocked by production issues. Which means that data scientists have to help deploy and maintain their models, which is costly and takes away from doing new data science.
What if there was a better way? Machine Learning Operations (MLOps) will get your AI projects out of the lab and into production where they can generate value and help transform your business. In this installment of four Data Science Central Podcasts on MLOps, we explore best practices in Production Model Monitoring.
Sivan Metzger, Managing Director, ML Ops & Governance – DataRobot
Sean Welch, Host and Producer – Data Science Central