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AIM216-R: [NEW LAUNCH!] Amazon SageMaker Debugger: Insights into ML model

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Manage episode 276820448 series 2819993
Content provided by John Rotenstein. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by John Rotenstein 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.
During ML model training, it's challenging to ensure that models are progressively learning the correct values for different parameters and to analyze and debug model characteristics without building additional tools, making the process time-consuming and cumbersome. Come learn about Amazon SageMaker Debugger, a new capability that provides complete insights into the training process by automating data capture and analysis from training runs without code changes. Learn how you can analyze data using the Amazon SageMaker Studio visual interface and be alerted when anomalies and errors are detected, reducing the time needed to debug models from days to minutes. Amazon SageMaker Debugger helps you solve problems quickly, reduce troubleshooting time during training, and build high-quality models.
  continue reading

520 episodes

Artwork
iconShare
 
Manage episode 276820448 series 2819993
Content provided by John Rotenstein. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by John Rotenstein 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.
During ML model training, it's challenging to ensure that models are progressively learning the correct values for different parameters and to analyze and debug model characteristics without building additional tools, making the process time-consuming and cumbersome. Come learn about Amazon SageMaker Debugger, a new capability that provides complete insights into the training process by automating data capture and analysis from training runs without code changes. Learn how you can analyze data using the Amazon SageMaker Studio visual interface and be alerted when anomalies and errors are detected, reducing the time needed to debug models from days to minutes. Amazon SageMaker Debugger helps you solve problems quickly, reduce troubleshooting time during training, and build high-quality models.
  continue reading

520 episodes

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