Enable CI/CD of multi-Region Amazon SageMaker endpoints

Favorite Amazon SageMaker and SageMaker inference endpoints provide a capability of training and deploying your AI and machine learning (ML) workloads. With inference endpoints, you can deploy your models for real-time or batch inference. The endpoints support various types of ML models hosted using AWS Deep Learning Containers or your

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Shared by AWS Machine Learning October 20, 2022

On the emerging landscape of open AI

Favorite By Alek Tarkowski The launch of open models like BLOOM and Stable Diffusion is a… The post On the emerging landscape of open AI first appeared on Voices of Open Source. Click Here to View Original Source (opensource.org)

Design patterns for serial inference on Amazon SageMaker

Favorite As machine learning (ML) goes mainstream and gains wider adoption, ML-powered applications are becoming increasingly common to solve a range of complex business problems. The solution to these complex business problems often requires using multiple ML models. These models can be sequentially combined to perform various tasks, such as

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Shared by AWS Machine Learning October 19, 2022

Implement RStudio on your AWS environment and access your data lake using AWS Lake Formation permissions

Favorite R is a popular analytic programming language used by data scientists and analysts to perform data processing, conduct statistical analyses, create data visualizations, and build machine learning (ML) models. RStudio, the integrated development environment for R, provides open-source tools and enterprise-ready professional software for teams to develop and share

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Shared by AWS Machine Learning October 19, 2022

Run ensemble ML models on Amazon SageMaker

Favorite Model deployment in machine learning (ML) is becoming increasingly complex. You want to deploy not just one ML model but large groups of ML models represented as ensemble workflows. These workflows are comprised of multiple ML models. Productionizing these ML models is challenging because you need to adhere to

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Shared by AWS Machine Learning October 18, 2022

Use Amazon SageMaker Canvas for exploratory data analysis

Favorite Exploratory data analysis (EDA) is a common task performed by business analysts to discover patterns, understand relationships, validate assumptions, and identify anomalies in their data. In machine learning (ML), it’s important to first understand the data and its relationships before getting into model building. Traditional ML development cycles can

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Shared by AWS Machine Learning October 18, 2022