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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM).

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Intelligent document processing with AWS AI and Analytics services in the insurance industry: Part 2

AWS Machine Learning

We also look into how to further use the extracted structured information from claims data to get insights using AWS Analytics and visualization services. We highlight on how extracted structured data from IDP can help against fraudulent claims using AWS Analytics services. Extraction phase. client('comprehend').

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3scale and Pivotal® Announce Self-serve API Management Solution Via Pivotal Web Services (PWS) Platform

Natalie Petouhof

Tweet Managing your API’s has become a very complicated endeavor. If your role to is manage API’s it’s important to figure out how to automate that process. Today 3scale and Pivotal ® announced that the 3scale self-serve API management solution is available through the Pivotal Web Services (PWS) platform.

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Elevate Your Call Center’s Performance with Speech Analytics

Talkdesk

Leveraging today’s innovative speech recognition technology and predictive analytics is the key to creating a customer-centric culture in the call center. Leveraging today’s innovative speech recognition technology and predictive analytics is the key to creating a customer-centric culture in the call center.”

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Elevate Your Call Center’s Performance with Speech Analytics

Talkdesk

Leveraging today’s innovative speech recognition technology and predictive analytics is the key to creating a customer-centric culture in the call center. Leveraging today’s innovative speech recognition technology and predictive analytics is the key to creating a customer-centric culture in the call center.”

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­­Speed ML development using SageMaker Feature Store and Apache Iceberg offline store compaction

AWS Machine Learning

The offline store data is stored in an Amazon Simple Storage Service (Amazon S3) bucket in your AWS account. SageMaker Feature Store automatically builds an AWS Glue Data Catalog during feature group creation. Table formats provide a way to abstract data files as a table. You can also use the FeatureGroup().put_record

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Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

Homomorphic encryption is a new approach to encryption that allows computations and analytical functions to be run on encrypted data, without first having to decrypt it, in order to preserve privacy in cases where you have a policy that states data should never be decrypted.

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