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Honeywell: Delivering on the Power of Outlier Detection

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Manage episode 379514658 series 3279398
Content provided by Domino Data Lab. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Lab 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://ppacc.player.fm/legal.
Every organization has an abundance of outlier detection use cases, but how do you turn them into repeatable, scalable AI products that drive a virtuous cycle of adoption and impact?
To answer this question, Jan Zirnstein, Senior Data Science Director at Honeywell,. shares their best practices for successfully driving value using anomaly detection, how to build trust with stakeholders, and the importance of both product management and software development resources.
Join us as we discuss:
  • How to spark a virtuous cycle with anomaly detection use cases
  • Driving continuous improvement by transitioning from unsupervised to supervised machine learning
  • Aligning the model development and software development lifecycles

  continue reading

97 episodes

Artwork
iconShare
 
Manage episode 379514658 series 3279398
Content provided by Domino Data Lab. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Domino Data Lab 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://ppacc.player.fm/legal.
Every organization has an abundance of outlier detection use cases, but how do you turn them into repeatable, scalable AI products that drive a virtuous cycle of adoption and impact?
To answer this question, Jan Zirnstein, Senior Data Science Director at Honeywell,. shares their best practices for successfully driving value using anomaly detection, how to build trust with stakeholders, and the importance of both product management and software development resources.
Join us as we discuss:
  • How to spark a virtuous cycle with anomaly detection use cases
  • Driving continuous improvement by transitioning from unsupervised to supervised machine learning
  • Aligning the model development and software development lifecycles

  continue reading

97 episodes

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