About this episode
Bret and Nirmal are joined by Maria Vechtomova, a MLOps Tech Lead and co-founder of Marvelous MLOps, to discuss the obvious and not-so obvious differences between a MLOps Engineer and traditional DevOps jobs.š My next course is coming soon! I've opened the waitlist for those wanting to go deep in GitHub Actions for DevOps and AI automation. I'm so thrilled to announce this course. The waitlist allows you to quickly sign up for some content updates, discounts, and more as I finish building the course. https://www.bretfisher.com/waitlistš¾Maria is here to discuss how DevOps engineers can adopt and operate machine learning workloads, also known as MLOps. With her expertise, we'll explore the challenges and best practices for implementing ML in a DevOps environment, including some hot takes on using Kubernetes.There's also a video version to watch on YouTube. ā
Topicsā
Marvelous MLOps on LinkedInMarvelous MLOps SubstackMarvelous MLOps YouTube ChannelCreators & Guests
Cristi Cotovan - Editor
Beth Fisher - Producer
Bret Fisher - Host
Maria Vechtomova - Guest
Nirmal Mehta - Host
(00:00) - Intro
(02:04) - Maria's Content
(03:22) - Tools and Technologies in MLOps
(09:21) - DevOps vs MLOps: Key Differences
(19:22) - Transitioning from DevOps to MLOps
(22:52) - Model Accuracy vs Computational Efficiency
(24:46) - MLOps with Sensitive Data
(29:10) - MLOps Roadmap and Getting Started
(32:36) - Tools and Platforms for MLOps
(37:14) - Adapting MLOps Practices to Future Trends
(44:08) - Is Golang an Option for CI/CD Automation?
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