Remove 2013 Remove Big data Remove Management Remove Metrics
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Contact Center Trends 2021: The CX Watershed

Fonolo

To achieve that within a remote or hybrid work environment, we’re going to see more contact centers reach for a cloud-based technology that drives camaraderie, increases visibility, allows supervisors to coach from anywhere, and enables agents to self-manage.” Managing a contact center has a unique set of challenges.

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Do You Use the Right Measures for Your CX?

Beyond Philosophy

What gets measured gets managed. The Types of Data for Your Metrics. Peppers says there are two different types of data that feed your metrics: Voice of Customer (VOC) Data: Peppers calls these metrics interactive data, meaning your customer interacts with you through a poll.

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Monitor embedding drift for LLMs deployed from Amazon SageMaker JumpStart

AWS Machine Learning

You can deploy each of these models through SageMaker JumpStart from the AWS Management Console , Amazon SageMaker Studio , or programmatically. For instructions, refer to Connect to your Linux instance with AWS Systems Manager Session Manager. For more information, refer to How to use JumpStart foundation models.

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The Top 7 Call Center Quality Assurance Software Solutions

Voxjar

Scorebuddy also offers a learning management solution and they recently added text analytics in order to search chat, support tickets, and more. Their platform includes a learning management system and allows you to survey your agents to measure their satisfaction. Founded in 2013. Founded in 2001. Based in Dublin Ireland.

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning

SageMaker Experiments is a capability of SageMaker that lets you create, manage, analyze, and compare your ML experiments. Active tidying up the environment, such as deleting unused instances, stopping unnecessary services, and removing temporary data, contributes to a clean and organized infrastructure.

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Designing generative AI workloads for resilience

AWS Machine Learning

Observability Besides the resource metrics you typically collect, like CPU and RAM utilization, you need to closely monitor GPU utilization if you host a model on Amazon SageMaker or Amazon Elastic Compute Cloud (Amazon EC2). He entered the big data space in 2013 and continues to explore that area.

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Generating value from enterprise data: Best practices for Text2SQL and generative AI

AWS Machine Learning

NLP SQL enables business users to analyze data and get answers by typing or speaking questions in natural language, such as the following: “Show total sales for each product last month” “Which products generated more revenue?” In entered the Big Data space in 2013 and continues to explore that area.