Tag: ML Models
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Your guide to AI/ML at AWS re:Invent 2022
AWS re:Invent season is upon us again! Just a few days to go until re:Invent takes place for the 11th year in Las Vegas,...
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...
How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants
Yara is the world’s leading crop nutrition company and a provider of environmental and agricultural solutions. Yara’s ambition is focused on growing a nature-positive...
Build high performing image classification models using Amazon SageMaker JumpStart
Image classification is a computer vision-based machine learning (ML) technique that allows you to classify images. Some well-known examples of image classification include classifying...
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...
New Amazon HealthLake capabilities enable next-generation imaging solutions and precision health analytics
At AWS, we have been investing in healthcare since Day 1 with customers including Moderna, Rush University Medical Center, and the NHS who have built...
Identifying and avoiding common data issues while building no code ML models with Amazon SageMaker Canvas
Business analysts work with data and like to analyze, explore, and understand data to achieve effective business outcomes. To address business problems, they often...
Serve multiple models with Amazon SageMaker and Triton Inference Server
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. It helps data scientists and developers prepare, build, train,...
Run inference at scale for OpenFold, a PyTorch-based protein folding ML model, using Amazon EKS
This post was co-written with Sachin Kadyan, a leading developer of OpenFold. In drug discovery, understanding the 3D structure of proteins is key to assessing the ability of a drug to bind to it, directly impacting its efficacy. Predicting the 3D protein form, however, is very complex, challenging, expensive, and time consuming, and can take […]
Optimize customer engagement with reinforcement learning
This is a guest post co-authored by Taylor Names, Staff Machine Learning Engineer, Dev Gupta, Machine Learning Manager, and Argie Angeleas, Senior Product Manager at Ibotta. Ibotta is an American technology company that enables users with its desktop and mobile apps to earn cash back on in-store, mobile app, and online purchases with receipt submission, […]
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