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An Introduction to the MLOps Tool Evaluation Rubric

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Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff 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://ro.player.fm/legal.

Organizations looking to build and adopt artificial intelligence (AI)–enabled systems face the challenge of identifying the right capabilities and tools to support Machine Learning Operations (MLOps) pipelines. Navigating the wide range of available tools can be especially difficult for organizations new to AI or those that have not yet deployed systems at scale. This webcast introduces the MLOps Tool Evaluation Rubric, designed to help acquisition teams pinpoint organizational priorities for MLOps tooling, customize rubrics to evaluate those key capabilities, and ultimately select tools that will effectively support ML developers and systems throughout the entire lifecycle, from exploratory data analysis to model deployment and monitoring. This webcast will walk viewers through the rubric's design and content, share lessons learned from applying the rubric in practice, and conclude with a brief demo.

What Attendees Will Learn:

• How to identify and prioritize key capabilities for MLOps tooling within their organizations

• How to customize and apply the MLOps Tool Evaluation Rubric to evaluate potential tools effectively

• Best practices and lessons learned from real-world use of the rubric in AI projects

  continue reading

174 episoade

Artwork
iconDistribuie
 
Manage episode 489496433 series 1264075
Content provided by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Carnegie Mellon University Software Engineering Institute and SEI Members of Technical Staff 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://ro.player.fm/legal.

Organizations looking to build and adopt artificial intelligence (AI)–enabled systems face the challenge of identifying the right capabilities and tools to support Machine Learning Operations (MLOps) pipelines. Navigating the wide range of available tools can be especially difficult for organizations new to AI or those that have not yet deployed systems at scale. This webcast introduces the MLOps Tool Evaluation Rubric, designed to help acquisition teams pinpoint organizational priorities for MLOps tooling, customize rubrics to evaluate those key capabilities, and ultimately select tools that will effectively support ML developers and systems throughout the entire lifecycle, from exploratory data analysis to model deployment and monitoring. This webcast will walk viewers through the rubric's design and content, share lessons learned from applying the rubric in practice, and conclude with a brief demo.

What Attendees Will Learn:

• How to identify and prioritize key capabilities for MLOps tooling within their organizations

• How to customize and apply the MLOps Tool Evaluation Rubric to evaluate potential tools effectively

• Best practices and lessons learned from real-world use of the rubric in AI projects

  continue reading

174 episoade

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