Laying an ML Ops Foundation: A Fireside Chat with Featured Speaker Mike Gualtieri

While you have hired top-notch data scientists to build models and invested in data science tools, you still can’t get your AI projects off the ground. Research shows that the share of AI models created but never put into production is anywhere between 50 and 90%. So what can teams do to gain value from AI?

The practice of Machine Learning Operations (MLOps) or ModelOps solves this challenge by bridging the gap between data teams and IT Ops teams, providing the capabilities that both teams need to work together to deploy, monitor, manage, and govern machine learning models in production. In this fireside chat, Featured Speaker Mike Gualtieri, VP, Principal Analyst at Forrester, will provide insight into what MLOps is and how any organization can use it to finally derive value from machine learning projects.

Attendees will learn:

• Best practices required for successful and sustained deployment of machine learning in production
• The importance of managing the dynamic nature of machine learning applications
• Why a strong MLOps strategy is required to enforce governance policies