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How Vericast optimized feature engineering using Amazon SageMaker Processing

AWS Machine Learning Blog

Each business problem is different, each dataset is different, data volumes vary wildly from client to client, and data quality and often cardinality of a certain column (in the case of structured data) might play a significant role in the complexity of the feature engineering process.

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Building Generative AI and ML solutions faster with AI apps from AWS partners using Amazon SageMaker

AWS Machine Learning Blog

SageMaker AI makes sure that sensitive data stays completely within each customer’s SageMaker environment and will never be shared with a third party. Their validation capabilities include automatic scoring, version comparison, and auto-calculated metrics for properties such as relevance, coverage, and grounded-in-context.

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