MLOps in Action: Real-World Examples for Establishing Best Practices

On-Demand | 45 Min

Machine learning (ML) has completely revolutionized the modern business enterprise. But to ensure ML functions can operate efficiently — and on a consistent, easy-to-replicate basis — global organizations must adhere to an effective MLOps strategy. If they don’t, they’ll miss out on the critical ROI of their machine learning capabilities.

While MLOps is a prolific topic of discussion, the truth is many MLOps efforts fall short in practice. So, how can the global enterprise ensure its machine learning efforts deliver on the promise of value?

Simple: By having the right strategy.

Join MLOps experts Brian Ray and Jose Ochoa for this on-demand presentation followed by an audience Q&A. Don’t miss this opportunity to learn from our experts and get answers to your burning MLOps questions.

Watch on Demand

During the presentation, we explore:

  •  Real-world examples of MLOps best practices
  •  Strategies for implementing your own MLOps plan of action
  •  Potential challenges and pitfalls that occur along the way


Brian Ray
Managing Director, AI / ML

Maven Wave, an Atos Company

Jose Ochoa
Solutions Engineer, AI / ML
Maven Wave, an Atos Company