Create high-quality data for ML models with Amazon SageMaker Ground Truth

Favorite Machine learning (ML) has improved business across industries in recent years—from the recommendation system on your Prime Video account, to document summarization and efficient search with Alexa’s voice assistance. However, the question remains of how to incorporate this technology into your business. Unlike traditional rule-based methods, ML automatically infers

Read More
Shared by AWS Machine Learning October 4, 2022

Achieve four times higher ML inference throughput at three times lower cost per inference with Amazon EC2 G5 instances for NLP and CV PyTorch models

Favorite Amazon Elastic Compute Cloud (Amazon EC2) G5 instances are the first and only instances in the cloud to feature NVIDIA A10G Tensor Core GPUs, which you can use for a wide range of graphics-intensive and machine learning (ML) use cases. With G5 instances, ML customers get high performance and

Read More
Shared by AWS Machine Learning October 3, 2022

Build flexible and scalable distributed training architectures using Kubeflow on AWS and Amazon SageMaker

Favorite In this post, we demonstrate how Kubeflow on AWS (an AWS-specific distribution of Kubeflow) used with AWS Deep Learning Containers and Amazon Elastic File System (Amazon EFS) simplifies collaboration and provides flexibility in training deep learning models at scale on both Amazon Elastic Kubernetes Service (Amazon EKS) and Amazon

Read More
Shared by AWS Machine Learning October 1, 2022

AWS Panorama now supports NVIDIA JetPack SDK 4.6.2

Favorite AWS Panorama is a collection of machine learning (ML) devices and a software development kit (SDK) that brings computer vision to on-premises internet protocol (IP) cameras. AWS Panorama device options include the AWS Panorama Appliance and the Lenovo ThinkEdge SE70, powered by AWS Panorama. These device options provide you

Read More
Shared by AWS Machine Learning October 1, 2022

How Sophos trains a powerful, lightweight PDF malware detector at ultra scale with Amazon SageMaker

Favorite This post is co-authored by Salma Taoufiq and Harini Kannan from Sophos. As a leader in next-generation cybersecurity, Sophos strives to protect more than 500,000 organizations and millions of customers across over 150 countries against evolving threats. Powered by threat intelligence, machine learning (ML), and artificial intelligence from Sophos

Read More
Shared by AWS Machine Learning September 30, 2022

Unified data preparation, model training, and deployment with Amazon SageMaker Data Wrangler and Amazon SageMaker Autopilot – Part 2

Favorite Depending on the quality and complexity of data, data scientists spend between 45–80% of their time on data preparation tasks. This implies that data preparation and cleansing take valuable time away from real data science work. After a machine learning (ML) model is trained with prepared data and readied

Read More
Shared by AWS Machine Learning September 30, 2022

Bundesliga Match Fact Win Probability: Quantifying the effect of in-game events on winning chances using machine learning on AWS

Favorite Ten years from now, the technological fitness of clubs will be a key contributor towards their success. Today we’re already witnessing the potential of technology to revolutionize the understanding of football. xGoals quantifies and allows comparison of goal scoring potential of any shooting situation, while xThreat and EPV models

Read More
Shared by AWS Machine Learning September 30, 2022