Remove 2012 Remove Clustering Remove Machine Learning
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Scale ML workflows with Amazon SageMaker Studio and Amazon SageMaker HyperPod

AWS Machine Learning Blog

Scaling machine learning (ML) workflows from initial prototypes to large-scale production deployment can be daunting task, but the integration of Amazon SageMaker Studio and Amazon SageMaker HyperPod offers a streamlined solution to this challenge. Tag the SageMaker HyperPod cluster with the key hyperpod-cluster-filesystem.

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Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI

AWS Machine Learning Blog

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning Blog

Exclusive to Amazon Bedrock, the Amazon Titan family of models incorporates 25 years of experience innovating with AI and machine learning at Amazon. With Amazon OpenSearch Serverless, you don’t need to provision, configure, and tune the instance clusters that store and index your data.

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Customize Amazon Nova in Amazon SageMaker AI using Direct Preference Optimization

AWS Machine Learning Blog

SageMaker uses the training job launcher script to run the Nova recipe on a managed compute cluster. Based on the selected recipe, SageMaker AI provisions the required infrastructure, orchestrates distributed training, and, upon completion, automatically decommissions the cluster. About the authors Mukund Birje is a Sr.

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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning Blog

jpg", "prompt": "Which part of Virginia is this letter sent from", "completion": "Richmond"} SageMaker JumpStart SageMaker JumpStart is a powerful feature within the SageMaker machine learning (ML) environment that provides ML practitioners a comprehensive hub of publicly available and proprietary foundation models (FMs).

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Transforming financial analysis with CreditAI on Amazon Bedrock: Octus’s journey with AWS

AWS Machine Learning Blog

Cost-efficiency and infrastructure optimization By moving away from GPU-based clusters to Fargate, our monthly infrastructure costs are now 78.47% lower, and our per-question costs have reduced by 87.6%. With a decade of experience at Amazon, having joined in 2012, Kshitiz has gained deep insights into the cloud computing landscape.

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Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

AWS Machine Learning Blog

Today, we’re excited to introduce a comprehensive approach to model evaluation through the Amazon Nova LLM-as-a-Judge capability on Amazon SageMaker AI , a fully managed Amazon Web Services (AWS) service to build, train, and deploy machine learning (ML) models at scale.

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