Get better insight from reviews using Amazon Comprehend

Favorite “85% of buyers trust online reviews as much as a personal recommendation” – Gartner Consumers are increasingly engaging with businesses through digital surfaces and multiple touchpoints. Statistics show that the majority of shoppers use reviews to determine what products to buy and which services to use. As per Spiegel

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Shared by AWS Machine Learning September 14, 2022

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

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

Deploy large models on Amazon SageMaker using DJLServing and DeepSpeed model parallel inference

Favorite The last few years have seen rapid development in the field of natural language processing (NLP). Although hardware has improved, such as with the latest generation of accelerators from NVIDIA and Amazon, advanced machine learning (ML) practitioners still regularly encounter issues deploying their large language models. Today, we announce

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Shared by AWS Machine Learning September 10, 2022

Improve transcription accuracy of customer-agent calls with custom vocabulary in Amazon Transcribe

Favorite Many AWS customers have been successfully using Amazon Transcribe to accurately, efficiently, and automatically convert their customer audio conversations to text, and extract actionable insights from them. These insights can help you continuously enhance the processes and products that directly improve the quality and experience for your customers. In

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Shared by AWS Machine Learning September 8, 2022