Remove APIs Remove Events Remove Healthcare Remove Personalization
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Build a news recommender application with Amazon Personalize

AWS Machine Learning

Delivering personalized news and experiences to readers can help solve this problem, and create more engaging experiences. However, delivering truly personalized recommendations presents several key challenges: Capturing diverse user interests – News can span many topics and even within specific topics, readers can have varied interests.

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

AWS Machine Learning

Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. Customer context Philips uses AI in various domains, such as imaging, diagnostics, therapy, personal health, and connected care.

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Analyze and tag assets stored in Veeva Vault PromoMats using Amazon AppFlow and Amazon AI Services

AWS Machine Learning

In a previous post , we talked about analyzing and tagging assets stored in Veeva Vault PromoMats using Amazon AI services and the Veeva Vault Platform’s APIs. In addition to the no-code interface, Amazon AppFlow supports configuration via API, AWS CLI, and AWS CloudFormation interfaces.

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Detect real and live users and deter bad actors using Amazon Rekognition Face Liveness

AWS Machine Learning

Financial services, the gig economy, telco, healthcare, social networking, and other customers use face verification during online onboarding, step-up authentication, age-based access restriction, and bot detection. This can deter a bad actor using social media pictures of another person to open fraudulent bank accounts.

APIs 77
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Face-off Probability, part of NHL Edge IQ: Predicting face-off winners in real time during televised games

AWS Machine Learning

Predicting face-off probability in real-time broadcasts can be broken down into two specific sub-problems: Modeling the face-off event as an ML problem, understanding the requirements and limitations, preparing the data, engineering the data signals, exploring algorithms, and ensuring reliability of results.

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Text Messaging Is Still Alive and Kicking after 25 Years

LiveChat

And this just covers my person. Issues with scalability, which were once a major concern for businesses taking up SMS marketing, have now been overcome by advancements in the application-to-person sector. Event registration and RSVPs. There’s a consensus that new technology will phase out the old. Limited time specials.

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New Amazon HealthLake capabilities enable next-generation imaging solutions and precision health analytics

AWS Machine Learning

At AWS, we have been investing in healthcare since Day 1 with customers including Moderna, Rush University Medical Center, and the NHS who have built breakthrough innovations in the cloud. At Radboud University Medical Center, our mission is to be a pioneer in shaping a more person-centered, innovative future of healthcare.