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 isolate resources, contain security threats and simplify billing-and data science pipelines are no different. At AWS, we’re continuing to innovate to simplify the MLOps workflow. In this post, we discuss some […]
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...
This article was published as a part of the Data Science Blogathon.
Introduction
Nowadays, a lot of data is being generated and consumed, resulting in a...
Today, we are launching Amazon SageMaker inference on AWS Graviton to enable you to take advantage of the price, performance, and efficiency benefits that come from Graviton chips. Graviton-based instances are available for model inference in SageMaker. This post helps you migrate and deploy a machine learning (ML) inference workload from x86 to Graviton-based instances […]
This post was co-authored by Arun Gupta, the Director of Business Intelligence at Prodege, LLC. Prodege is a data-driven marketing and consumer insights platform comprised of consumer brands—Swagbucks, MyPoints, Tada, ySense, InboxDollars, InboxPounds, DailyRewards, PollFish, and Upromise—along with a complementary suite of business solutions for marketers and researchers. Prodege has 120 million users and has […]
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. It helps data scientists and developers prepare, build, train,...
Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to quickly build, train, and deploy machine learning (ML)...
