AWS HPC Blog

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Improving NFL player health using machine learning with AWS Batch

Improving NFL player health using machine learning with AWS Batch

In this post we’ll show you how the NFL used AWS to scale their ML workloads and produce the first comprehensive dataset of helmet impacts across multiple NFL seasons. They were able to reduce manual labor by 90% and the results beats human labelers in accuracy by 12%!

Streamlining distributed ML workflow orchestration using Covalent with AWS Batch

Streamlining distributed ML workflow orchestration using Covalent with AWS Batch

Complicated multi-step workflows can be challenging to deploy, especially when using a variety of high-compute resources. Covalent is an open-source orchestration tool that streamlines the deployment of distributed workloads on AWS resources. In this post, we outline key concepts in Covalent and develop a machine learning workflow for AWS Batch in just a handful of steps.

Building a 4x faster and scalable algorithm using AWS Batch for Amazon Logistics

Building a 4x faster and more scalable algorithm using AWS Batch for Amazon Logistics

In this post, AWS Professional Services highlights how they helped data scientists from Amazon Logistics rearchitect their algorithm for improving the efficiency of their supply-chain by making better planning decisions. Leveraging best practices for deploying scalable HPC applications on AWS, the teams saw a 4X improvement in run time.