Deploying ML models using SageMaker Serverless Inference (Preview)

Favorite Amazon SageMaker Serverless Inference (Preview) was recently announced at re:Invent 2021 as a new model hosting feature that lets customers serve model predictions without having to explicitly provision compute instances or configure scaling policies to handle traffic variations. Serverless Inference is a new deployment capability that complements SageMaker’s existing

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Shared by AWS Machine Learning January 5, 2022

Identity verification using Amazon Rekognition

Favorite In-person user identity verification is slow to scale, costly, and high friction for users. Machine learning (ML) powered facial recognition technology can enable online user identity verification. Amazon Rekognition offers pre-trained facial recognition capabilities that you can quickly add to your user onboarding and authentication workflows to verify opted-in

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Shared by AWS Machine Learning January 4, 2022

Train graph neural nets for millions of proteins on Amazon SageMaker and Amazon DocumentDB (with MongoDB compatibility)

Favorite There are over 180,000 unique proteins with 3D structures determined, with tens of thousands new structures resolved every year. This is only a small fraction of the 200 million known proteins with distinctive sequences. Recent deep learning algorithms such as AlphaFold can accurately predict 3D structures of proteins using

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Shared by AWS Machine Learning January 4, 2022

Introducing hybrid machine learning

Favorite Gartner predicts that by the end of 2024, 75% of enterprises will shift from piloting to operationalizing artificial intelligence (AI), and the vast majority of workloads will end up in the cloud in the long run. For some enterprises that plan to migrate to the cloud, the complexity, magnitude,

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Shared by AWS Machine Learning December 24, 2021