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#393: ML Explainability using Amazon SageMaker Debugger

#393: ML Explainability using Amazon SageMaker Debugger

FromAWS Podcast


#393: ML Explainability using Amazon SageMaker Debugger

FromAWS Podcast

ratings:
Length:
28 minutes
Released:
Sep 20, 2020
Format:
Podcast episode

Description

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/
Released:
Sep 20, 2020
Format:
Podcast episode

Titles in the series (100)

The AWS Podcast is the definitive cloud platform podcast for developers, dev ops, and cloud professionals seeking the latest news and trends in storage, security, infrastructure, serverless, and more. Join Simon Elisha and Jeff Barr for regular updates, deep dives and interviews. Whether you’re building machine learning and AI models, open source projects, or hybrid cloud solutions, the AWS Podcast has something for you.