Remove AWS Remove Clustering Remove Definition
article thumbnail

Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC

AWS Machine Learning Blog

Starting with the AWS Neuron 2.18 release , you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers) with the latest released Neuron packages on the same day as the Neuron SDK release. AWS DLCs provide a set of Docker images that are pre-installed with deep learning frameworks.

AWS 131
article thumbnail

Deploy Amazon SageMaker pipelines using AWS Controllers for Kubernetes

AWS Machine Learning Blog

A challenge for DevOps engineers is the additional complexity that comes from using Kubernetes to manage the deployment stage while resorting to other tools (such as the AWS SDK or AWS CloudFormation ) to manage the model building pipeline. kubectl for working with Kubernetes clusters. eksctl for working with EKS clusters.

AWS 114
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Scale your machine learning workloads on Amazon ECS powered by AWS Trainium instances

AWS Machine Learning Blog

With containers, scaling on a cluster becomes much easier. In late 2022, AWS announced the general availability of Amazon EC2 Trn1 instances powered by AWS Trainium accelerators, which are purpose built for high-performance deep learning training. Create a task definition to define an ML training job to be run by Amazon ECS.

AWS 114
article thumbnail

Revolutionizing earth observation with geospatial foundation models on AWS

Flipboard

It also comes with ready-to-deploy code samples to help you get started quickly with deploying GeoFMs in your own applications on AWS. For a full architecture diagram demonstrating how the flow can be implemented on AWS, see the accompanying GitHub repository. Lets dive in! Solution overview At the core of our solution is a GeoFM.

AWS 116
article thumbnail

Ray jobs on Amazon SageMaker HyperPod: scalable and resilient distributed AI

AWS Machine Learning Blog

At its core, Ray offers a unified programming model that allows developers to seamlessly scale their applications from a single machine to a distributed cluster. A Ray cluster consists of a single head node and a number of connected worker nodes. Ray clusters and Kubernetes clusters pair well together.

article thumbnail

How Aetion is using generative AI and Amazon Bedrock to unlock hidden insights about patient populations

AWS Machine Learning Blog

Smart Subgroups For a user-specified patient population, the Smart Subgroups feature identifies clusters of patients with similar characteristics (for example, similar prevalence profiles of diagnoses, procedures, and therapies). The AML feature store standardizes variable definitions using scientifically validated algorithms.

article thumbnail

Build enterprise-ready generative AI solutions with Cohere foundation models in Amazon Bedrock and Weaviate vector database on AWS Marketplace

AWS Machine Learning Blog

We demonstrate how to build an end-to-end RAG application using Cohere’s language models through Amazon Bedrock and a Weaviate vector database on AWS Marketplace. Additionally, you can securely integrate and easily deploy your generative AI applications using the AWS tools you are already familiar with.

AWS 144