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MLOps for DevOps People

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Manage episode 438453184 series 2483573
Content provided by Bret Fisher. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Bret Fisher or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.
Maria 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.

Be sure to check out the live recording of the complete show from June 20, 2024 on YouTube (Stream 271).

★Topics★
Marvelous MLOps on LinkedIn
Marvelous MLOps Substack
Marvelous MLOps YouTube Channel

Creators & Guests

  • (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?

You can also support my free material by subscribing to my YouTube channel and my weekly newsletter at bret.news!

Grab the best coupons for my Docker and Kubernetes courses.
Join my cloud native DevOps community on Discord.
Grab some merch at Bret's Loot Box
Homepage bretfisher.com

  continue reading

172 episodes

Artwork
iconShare
 
Manage episode 438453184 series 2483573
Content provided by Bret Fisher. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Bret Fisher or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

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.
Maria 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.

Be sure to check out the live recording of the complete show from June 20, 2024 on YouTube (Stream 271).

★Topics★
Marvelous MLOps on LinkedIn
Marvelous MLOps Substack
Marvelous MLOps YouTube Channel

Creators & Guests

  • (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?

You can also support my free material by subscribing to my YouTube channel and my weekly newsletter at bret.news!

Grab the best coupons for my Docker and Kubernetes courses.
Join my cloud native DevOps community on Discord.
Grab some merch at Bret's Loot Box
Homepage bretfisher.com

  continue reading

172 episodes

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