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Mastering Escalation Management: Harnessing Tech in Modern Call Centers

NobelBiz

According to Forbes, call center metrics are the data harvested from all the solutions used to operate a call center, such as call center management (CCM) and customer relationship management (CRM) platforms. By analyzing this data in real-time, they can quickly identify patterns or trends that may indicate areas for improvement.

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Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

AWS Machine Learning

The player data was used to derive features for model development: X – Player position along the long axis of the field Y – Player position along the short axis of the field S – Speed in yards/second; replaced by Dis*10 to make it more accurate (Dis is the distance in the past 0.1

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A 5-Step Checklist for Mastering Enterprise AI

CSM Magazine

Whenever a new iteration of the AI tool is released, remember to monitor key metrics that reflect and reinforce your original goals such as ‘What % of users engage with the assistant?’, ‘What are the most popular topics?’ How many visitors request transfer to a live agent?’ For more information, please visit www.ebi.ai.

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Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning

Data Lake Architect with AWS Professional Services. She is passionate about solving customer pain points processing big data and providing long-term scalable solutions. Prior to this role, she developed products in internet, telecom, and automotive domains, and has been an AWS customer.

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The Guide to AI in Customer Experience

SmartKarrot

The power of AI, ML, and big data has facilitated a decision-making metric. In contrast, decisions should depend on data. It leads to an enormous change in the decision-making strategies of the health, financial services, and automotive sectors.

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

AWS Machine Learning

He entered the big data space in 2013 and continues to explore that area. Her specialization is machine learning, and she is actively working on designing solutions using various AWS ML, big data, and analytics offerings. He also holds an MBA from Colorado State University.

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Accelerating AI/ML development at BMW Group with Amazon SageMaker Studio

AWS Machine Learning

Both the workspace and portal are monitored using Amazon CloudWatch logs, metrics, and alarms to check key performance indicators (KPIs) and proactively notify the platform team of any issues. In his free time, Joaquin enjoys spending time with family and reading science-fiction novels.