Category: Amazon Machine Learning

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, […]

中文版 – 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 […]

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 […]

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 and improvements in the form of pull requests. We have now added over 138 additional developer and user guides […]