EP74: AI/ML en AWS: Sesgo y explicabilidad en modelos de machine learning

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Recorded19 Nov 2021

Publisherrss.art19.com

Handlerec:13454002

Show notes

En este episodio, Rodrigo Alarcón y Enrique Rodríguez conversan sobre algunos de los actuales desafíos en materia de detección de sesgos y explicabilidad en modelos de machine learning. Además explican cómo los científicos de datos pueden abordar este tipo de desafíos al momento de construir sus modelos, usando SageMaker Clarify. Material Adicional: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-fairness-and-explainability.html

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