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Intersecting DevOps With the ML Lifecycle with Shirsha Ray Chaudhuri

Podcast |: MLOps Live
Publisher |: neptune.ai
Media Type |: audio
Podknife tags |: Artificial Intelligence,; Interview,; Machine Learning,; Technology
Categories Via RSS |: Technology
Publication Date |: Dec 21, 2022
Episode Duration |: 00:49:20

Description
Content Encoded

In this episode of MLOps Live, Stephen is joined by Shirsha Ray C, Director of Engineering at TR Labs. Shirsha discusses standards and best practices for delivering ML solutions with DevOps and explores metrics to measure performance using AWS tooling, as well as data scientists' understanding of why ML models are used and their dream state for DevOps. They also discuss challenges faced in deploying ML systems and some best practices to bridge the gap between DevOps and ML teams.

Subscribe to our YouTube channel to watch this episode!

Learn more about Shirsha Ray Chaudhuri:

Shirsha's LinkedIn

Episode Resources:

Shirsha's Publication
TR Labs' thomson-reuters-labs.html">Website

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To learn more visit Neptune.ai

Previous guests include: Andy McMahon of NatWest Group, Jacopo Tagliabue of Coveo, Adam Sroka of Origami, Amber Roberts of Arize AI, Michal Tadeusiak of deepsense.ai, Danny Leybzon of WhyLabs, Kyle Morris of Banana ML, Federico Bianchi of Università Bocconi, Mateusz Opala of Brainly, Kuba Cieslik of tuul.ai, Adam Becker of Telepath.io and Fernando Rejon & Jakub Zavrel of Zeta Alpha Vector. Check out our three most downloaded episodes:

MLOps Live is handcrafted by our friends over at: fame.so

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