#393: ML Explainability using Amazon SageMaker Debugger -...

What this episode covers

This episode discusses the growing need for machine learning explainability across various business verticals. Then it introduces Amazon SageMaker Debugger, a service that provides visibility into the ML model training process for real-time and offline analysis. https://aws.amazon.com/blogs/aws/amazon-sagemaker-debugger-debug-your-machine-learning-models/

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Frequently Asked Questions

How long is this episode of AWS Podcast?

This episode is 28 minutes long.

When was this AWS Podcast episode published?

This episode was published on September 20, 2020.

What is this episode about?

This episode discusses the growing need for machine learning explainability across various business verticals. Then it introduces Amazon SageMaker Debugger, a service that provides visibility into the ML model training process for real-time and...

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