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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management. He received my Ph.D.

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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning

The combination of large language models (LLMs), including the ease of integration that Amazon Bedrock offers, and a scalable, domain-oriented data infrastructure positions this as an intelligent method of tapping into the abundant information held in various analytics databases and data lakes.

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Recommend top trending items to your users using the new Amazon Personalize recipe

AWS Machine Learning

You can get started without any prior ML experience, using APIs to easily build sophisticated personalization capabilities in a few clicks. On the campaign ( trending-now-campaign ) Personalization API tab, choose Get recommendations. The following table is a sample after mapping the IDs to the actual movie titles for readability.

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How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart

AWS Machine Learning

This post was written with Darrel Cherry, Dan Siddall, and Rany ElHousieny of Clearwater Analytics. About Clearwater Analytics Clearwater Analytics (NYSE: CWAN) stands at the forefront of investment management technology. Crystal shares CWICs core functionalities but benefits from broader data sources and API access.

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CCaaS Trends: The Evolution of Cloud Contact Centres

Lumoa

These include customer service analytics, engagement hubs, the voice of the customer , virtual agents (live chat), and chatbots. Migration to the Cloud Buoyed by the COVID-19 outbreak, cloud migration dramatically increased during the steepest economic contraction since the 2008 financial crisis.

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A review of purpose-built accelerators for financial services

AWS Machine Learning

The financial services industry (FSI) is no exception to this, and is a well-established producer and consumer of data and analytics. This mostly non-technical post is written for FSI business leader personas such as the chief data officer, chief analytics officer, chief investment officer, head quant, head of research, and head of risk.

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Automated exploratory data analysis and model operationalization framework with a human in the loop

AWS Machine Learning

The sample dataset we use in this post is a sampled version of the Diabetes 130-US hospitals for years 1999-2008 Data Set (Beata Strack, Jonathan P. For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. His focus area is on data and analytics.