Category: Amazon Machine Learning

Today more and more companies are taking a personalized approach to content and marketing. For example, retailers are personalizing product recommendations and promotions for customers. An important step toward providing personalized recommendations is to identify a customer’s propensity to take action for a certain category. This propensity is based on a customer’s preferences and past […]

Customers on AWS deploy trained machine learning (ML) and deep learning (DL) models in production using Amazon SageMaker, and using other services such as AWS Lambda, AWS Fargate, AWS Elastic Beanstalk, and Amazon Elastic Compute Cloud (Amazon EC2) to name a few. Amazon SageMaker provides SDKs and a console-only workflow to deploy trained models, and […]

Many AWS customers—startups and large enterprises—are on a path to adopt machine learning and deep learning in their existing applications. The reasons for machine learning adoption are dictated by the pace of innovation in the industry, with business use cases ranging from customer service (including object detection from images and video streams, sentiment analysis) to […]

If you work in data science, you might think that the hardest thing about machine learning is not knowing when you’ll be done. You start with a problem, a dataset, and an idea about how to solve it, but you never know whether your approach is going to work until later, after you’ve wasted time. […]

I like prototyping on my laptop, as much as the next person. When I want to collaborate, I push my code to GitHub and invite collaborators. And when I want to run experiments and need more compute power, I rent CPU and GPU instances in the cloud, copy my code and dependencies over, and run […]

As the dust settles after another re:Invent closes, I wanted to put together a quick summary of all the open source-related announcements that happened in the run up to this year’s re:Invent and the week itself. If you are interested in open source in mobile web development, devops, containers, security, big data and data analytics, […]

Today, we announce the availability of Gluon Time Series (GluonTS), an Apache MXNet-based toolkit for time series analysis using the Gluon API. We are excited to give researchers and practitioners working with time series data access to this toolkit, which we have built for our own needs as applied scientists working on real-world industrial time […]

中文版 – In this post, we will demonstrate how to create a fully-managed Kubernetes cluster on AWS using Amazon Elastic Container Service for Kubernetes (Amazon EKS), and how to run distributed deep learning training jobs using Kubeflow and the AWS FSx CSI driver. We then will discuss best practices to optimize machine learning training performance […]

Open Source News from the AWS Summit San Francisco The AWS Summit in San Francisco on April 4th saw a slew of announcements, including some in open source: SAM Implementation is now open source! “In 2016, we launched SAM and opened up the SAM specification on this Github repo to invite collaborators. We’ve loved your […]

September 8, 2021: Amazon Elasticsearch Service has been renamed to Amazon OpenSearch Service. Visit the website to learn more. AWS Documentation is Now Open Source and On GitHub Earlier this year we made the AWS SDK developer guides available as GitHub repos (all found within the awsdocs organization) and invited interested parties to contribute changes […]