SageMaker Clarify
These examples provide an introduction to SageMaker Clarify which provides machine learning developers with greater visibility into their training data and models so they can identify and limit bias and explain predictions.
SageMaker Clarify Processing
- Fairness and Explainability with SageMaker Clarify
- Fairness and Explainability with SageMaker Clarify - JSON Lines Format
- Fairness and Explainability with SageMaker Clarify - Bring Your Own Container
- Fairness and Explainability with SageMaker Clarify - Spark Distributed Processing
- Fairness and Explainability with SageMaker Clarify using AWS SDK for Python (Boto3)
- Explaining text sentiment analysis using SageMaker Clarify
- Explaining Image Classification with SageMaker Clarify
- Explaining Object Detection model with Amazon SageMaker Clarify
- Credit risk prediction and explainability with Amazon SageMaker