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Software Engineering for Machine Learning: Characterizing and Understanding Mismatch in ML Systems

Software Engineering for Machine Learning: Characterizing and Understanding Mismatch in ML Systems

FromSoftware Engineering Institute (SEI) Podcast Series


Software Engineering for Machine Learning: Characterizing and Understanding Mismatch in ML Systems

FromSoftware Engineering Institute (SEI) Podcast Series

ratings:
Length:
30 minutes
Released:
Nov 18, 2021
Format:
Podcast episode

Description

Mismatches between the perspectives and practices of the roles involved in the development and fielding of ML systems—data scientists, software engineers, and operations personnel—can affect the ability of systems to achieve their intended missions. In this SEI Podcast, Grace Lewis, a principal researcher and lead for the Tactical and AI-Enabled Systems Initiative, and Ipek Ozkaya, technical director of Engineering Intelligent Software Systems, discuss their research into characterizing, codifying, and mitigating such mismatches.
Released:
Nov 18, 2021
Format:
Podcast episode

Titles in the series (100)

The SEI Podcast Series presents conversations in software engineering, cybersecurity, and future technologies.