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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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Governing ML lifecycle at scale: Best practices to set up cost and usage visibility of ML workloads in multi-account environments

AWS Machine Learning

For a multi-account environment, you can track costs at an AWS account level to associate expenses. A combination of an AWS account and tags provides the best results. For multiple accounts, assign mandatory tags to each one, identifying its purpose and the owner responsible.

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Supercharge your AI team with Amazon SageMaker Studio: A comprehensive view of Deutsche Bahn’s AI platform transformation

AWS Machine Learning

At Deutsche Bahn, a dedicated AI platform team manages and operates the SageMaker Studio platform, and multiple data analytics teams within the organization use the platform to develop, train, and run various analytics and ML activities. For high availability, multiple identical private isolated subnets are provisioned.

APIs 133
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Boost agent productivity with Salesforce integration for Live Call Analytics

AWS Machine Learning

The Live Call Analytics with Agent Assist (LCA) open-source solution addresses these challenges by providing features such as AI-powered agent assistance, call transcription, call summarization, and much more. An AWS account. Under Available OAuth Scopes , choose Manage user data via APIs (api). We’ve all been there.

Analytics 103
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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. Amazon Redshift is another service in the Analytics stack.

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Build a receipt and invoice processing pipeline with Amazon Textract

AWS Machine Learning

One area that holds significant potential for improvement is accounts payable. On a high level, the accounts payable process includes receiving and scanning invoices, extraction of the relevant data from scanned invoices, validation, approval, and archival. It is available both as a synchronous or asynchronous API.

APIs 127
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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.