How Medidata used Amazon SageMaker asynchronous inference to accelerate ML inference predictions up to 30 times faster

Favorite This post is co-written with Rajnish Jain, Priyanka Kulkarni and Daniel Johnson from Medidata. Medidata is leading the digital transformation of life sciences, creating hope for millions of patients. Medidata helps generate the evidence and insights to help pharmaceutical, biotech, medical devices, and diagnostics companies as well as academic

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Shared by AWS Machine Learning September 13, 2022

9 arguments for a Knowledge Management strategy

Favorite You need a strategy if your KM implementation is to be successful. Here are 8 reasons why. Implementing Knowledge Management without a strategy is a risky endeavour. As Sun Tzu is reputed to have said said, in “the art of war”, “Strategy without tactics is the slowest route to victory.

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Shared by Nick Milton September 12, 2022

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

Favorite This is a guest blog post cowritten with athenahealth. athenahealth a leading provider of network-enabled software and services for medical groups and health systems nationwide. Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its

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Shared by AWS Machine Learning September 10, 2022

Tips to improve your Amazon Rekognition Custom Labels model

Favorite In this post, we discuss best practices to improve the performance of your computer vision models using Amazon Rekognition Custom Labels. Rekognition Custom Labels is a fully managed service to build custom computer vision models for image classification and object detection use cases. Rekognition Custom Labels builds off of the

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Shared by AWS Machine Learning September 10, 2022