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Big Changes Need Big Data 

Playvox

SoFi’s QA team captures feedback from multiple support channels and communicates constructive coaching directly to agents, team leads, and managers. The SoFi team was able to streamline their QA forms during the Insights implementation stage to better target the data relevant to their immediate needs.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

The following diagram depicts an architecture for centralizing model governance using AWS RAM for sharing models using a SageMaker Model Group , a core construct within SageMaker Model Registry where you register your model version. The final step is to register the candidate model to the model group as a new model version.

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

AWS Machine Learning

Lior Perez is a Principal Solutions Architect on the construction team based in Toulouse, France. He enjoys supporting customers in their digital transformation journey, using big data, machine learning, and generative AI to help solve their business challenges.

APIs 124
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What Do The Pioneers of Customer Experience See for the Future: And What Should You Do About It?

Beyond Philosophy

Carbone’s primary philosophy works with constructs around Clue Consciousness, which describes how their unconscious processing of Customer Experience signals drives customer behavior. It appeals to me because it uses a data-driven approach. These clues affect our emotions, shape our attitudes, and guide our actions.

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How to Choose the Best Data Visualization Tools

Callminer

Big data is getting bigger with each passing year, but making sense of trends hidden deep in the heap of 1s and 0s is more confounding than ever. As metrics pile up, you may find yourself wondering which data points matter and in what ways they relate to your business’s interests. Two images can be better than one.

Big data 140
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Personalize your generative AI applications with Amazon SageMaker Feature Store

AWS Machine Learning

Building on the concept of dynamically fetching up-to-date data to produce personalized content, the use of LLMs has garnered significant attention in recent research for recommender systems. In summary, intelligent agents could construct prompts using user- and item-related data and deliver customized natural language responses to users.

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Define customized permissions in minutes with Amazon SageMaker Role Manager via the AWS CDK

AWS Machine Learning

with the following code: import * as cdk from 'aws-cdk-lib'; import { Construct } from 'constructs'; import * as iam from 'aws-cdk-lib/aws-iam'; import { Activity } from '@cdklabs/cdk-aws-sagemaker-role-manager'; export class RoleManagerStack extends cdk.Stack { constructor(scope: Construct, id: string, props?