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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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Performance Management Bridges the Divide Between Big Data and Big Knowledge

Aspect

There is information everywhere: in your ACD , WFM, CRM, quality management, recording, surveys, speech analytics and self-service systems. That’s exactly what Performance Management (PM) does in the contact center, but it’s a long road from information to knowledge.

Big data 102
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Governing the ML lifecycle at scale, Part 3: Setting up data governance at scale

AWS Machine Learning

This post dives deep into how to set up data governance at scale using Amazon DataZone for the data mesh. The data mesh is a modern approach to data management that decentralizes data ownership and treats data as a product. To view this series from the beginning, start with Part 1.

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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning

An AWS account and an AWS Identity and Access Management (IAM) principal with sufficient permissions to create and manage the resources needed for this application. If you don’t have an AWS account, refer to How do I create and activate a new Amazon Web Services account?

APIs 123
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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning

Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. Features are inputs to ML models used during training and inference.

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Use Amazon SageMaker pipeline sharing to view or manage pipelines across AWS accounts

AWS Machine Learning

On August 9, 2022, we announced the general availability of cross-account sharing of Amazon SageMaker Pipelines entities. You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls. Solution overview.

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Digital Transformation in Retail Banks: Potential Impact on Brand Equity, Customers, and Employees

Beyond Philosophy

I’m capitalizing the first letter of each word because the pervasiveness of digital transformation has all the feel of Big Data a few years ago and Reeingineering in the 1990’s. Much of the digital transformation emphasis has been on technology (big data analytics and cloud, mobile apps, etc.)

Banking 225