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Organize machine learning development using shared spaces in SageMaker Studio for real-time collaboration
Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). It provides a single, web-based visual interface where you...
Improve governance of your machine learning models with Amazon SageMaker
As companies are increasingly adopting machine learning (ML) for their mainstream enterprise applications, more of their business decisions are influenced by ML models. As...
Define customized permissions in minutes with Amazon SageMaker Role Manager
Administrators of machine learning (ML) workloads are focused on ensuring that users are operating in the most secure manner, striving towards a principal of...
Separate lines of business or teams with multiple Amazon SageMaker domains
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step...
Operationalize your Amazon SageMaker Studio notebooks as scheduled notebook jobs
Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In addition to...
Apply fine-grained data access controls with AWS Lake Formation and Amazon EMR from Amazon SageMaker Studio
Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) that enables data scientists and developers to perform every step...
AlexaTM 20B is now available in Amazon SageMaker JumpStart
Today, we announce the public availability of Amazon’s state-of-the-art Alexa Teacher Model with 20 billion parameters (AlexaTM 20B) through Amazon SageMaker JumpStart, SageMaker’s machine...
Large-scale feature engineering with sensitive data protection using AWS Glue interactive sessions and Amazon SageMaker Studio
Organizations are using machine learning (ML) and AI services to enhance customer experience, reduce operational cost, and unlock new possibilities to improve business outcomes....
Build a cross-account MLOps workflow using the Amazon SageMaker model registry
A well-designed CI/CD pipeline is essential to scale any software development workflow effectively. When designing production CI/CD pipelines, AWS recommends leveraging multiple accounts to...
Enabling hybrid ML workflows on Amazon EKS and Amazon SageMaker with one-click Kubeflow on AWS deployment
Today, many AWS customers are building enterprise-ready machine learning (ML) platforms on Amazon Elastic Kubernetes Service (Amazon EKS) using Kubeflow on AWS (an AWS-specific...
Malware detection and classification with Amazon Rekognition
According to an article by Cybersecurity Ventures, the damage caused by Ransomware (a type of malware that can block users from accessing their data...
Bank of the West Turns to Extend for Virtual Cards and Spend Management
Virtual card and spend management platform Extend announced a partnership with Bank of the West.The collaboration will enable small and medium-sized businesses to...
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