MLOps offers ways to optimize processes, automate workflows, detect anomalies, reduce costs, and improve business outcomes. However, implementing and applying these techniques can be a large and complex effort.

Join Anaconda's Chris Styduhar, Connor Grant, and Josh Burt to explore strategies for using MLOps to drive value from AI across the enterprise.

During this fireside chat, you will learn:

The ML lifecycle
Defining MLOps and its key components
How to drive high-performance MLOps in your organization
Model monitoring, keeping your models fresh and performant

Whether you're a data scientist, an IT professional, or a business leader, this event is a must-attend for anyone looking to harness the full potential of MLOps in their organization.

Register Now to Watch On-Demand

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Meet the Presenters!

Chris Styduhar

Product Management for AI/ML at Anaconda
Background ML / AI Strategy
Based in Salt Lake City, UT

Connor Gunn

Product Leader for Data Science Platform
Background in Data Science
Based in Austin, TX

Josh Burt

Software Engineering for Data Science Platform / MLOps
Background in Enterprise Software, Machine Learning
Based in Seattle, WA

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Meet the Presenters!

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