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

Detect audio events with Amazon Rekognition

Favorite When most people think of using machine learning (ML) with audio data, the use case that usually comes to mind is transcription, also known as speech-to-text. However, there are other useful applications, including using ML to detect sounds. Using software to detect a sound is called audio event detection,

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Shared by AWS Machine Learning September 7, 2022