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Americas FSI Digital Commentary: 3 Ways to Accelerate Digital Strategy in 2023

Cisco - Contact Center

As a change agent serving the financial services industry for over 20 years, it is a great privilege to collaborate with Bank, Insurance, and Wealth Management institutions to devise and execute digital transformation strategy, solve complex business problems, and leverage technology to strengthen business results.

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Build custom code libraries for your Amazon SageMaker Data Wrangler Flows using AWS Code Commit

AWS Machine Learning

Therefore, organizations have adopted technology best practices, including microservice architecture, MLOps, DevOps, and more, to improve delivery time, reduce defects, and increase employee productivity. This post introduces a best practice for managing custom code within your Amazon SageMaker Data Wrangler workflow.

Scripts 62
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Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. Maintainability – The platform’s architecture and code base should be well organized, modular, and maintainable.

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Build and train ML models using a data mesh architecture on AWS: Part 1

AWS Machine Learning

Typically, large financial services organizations have multiple LoBs, such as consumer banking, investment banking, and asset management, and also one or more analytics and ML CoE teams. Allow the consumer banking LoB to share data products into the central governance layer. Financial services use case.

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FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

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The 2021 Caller Authentication Guide for Contact Centers

pindrop

From email to bank logins, many companies have employed tools like two-factor verification to make their services more secure. Keep things simple with API integration whenever possible. Pindrop’s APIs are straightforward – the footprint is small, they’re effortless to use. CALLER AUTHENTICATION BEST PRACTICES.

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AWS Unveils New AI Service Features and Enhancements at re:Invent 2022

AWS Machine Learning

For example, WaFd Bank, a full-service US bank, improved its customer experience with Talkdesk (a global cloud contact center company) and AWS Contact Center Intelligence (CCI) solutions, reducing call times by up to 90%. Customers can use AWS AI services with no ML expertise required.