AWS Machine Learning Blog

This is a guest post by Mark Wood at Pulselive. In their own words, “Pulselive, based out of the UK, is the proud digital partner to some of the biggest names in sports.” At Pulselive, we create experiences sports fans can’t live without; whether that’s the official Cricket World Cup website or the English Premier […]

When you build models with the Apache MXNet deep learning framework, you can take advantage of the expansive model zoo provided by GluonCV to quickly train state-of-the-art computer vision algorithms for image and video processing. A typical development environment for training consists of a Jupyter notebook hosted on a compute instance configured by the operating […]

In this post you will compile an open-source TensorFlow version of OpenPose using AWS Neuron and fine tune its inference performance for AWS Inferentia based instances. You will set up a benchmarking environment, measure the image processing pipeline throughput, and quantify the price-performance improvements as compared to a GPU based instance. About OpenPose Human pose […]

As solutions architects working in Brazil, we often translate technical content from English to other languages. Doing so manually takes a lot of time, especially when dealing with presentations—in contrast to plain text documents, their content is spread across various areas in multiple slides. To solve that, we wrote a script that translates Microsoft PowerPoint […]

This is a guest post by the Jira Cloud Performance Team at Atlassian. In their own words, Atlassian’s mission is to unleash the potential in every team. Our products help teams organize, discuss, and complete their work. And what teams do can change the world. We have helped NASA teams design the Mars Rover, Cochlear teams develop […]

This is a guest post co-written by Sergio Delgado from YoucanBook.me. In their own words, “YouCanBook.me is a small, independent and fully remote team, who love solving scheduling problems all over the world.” At YoucanBook.me, we like to say that we’re “a small company that does great things.” Many aspects of our day-to-day culture are […]

This post is co-written by Femi Olumofin, an analytics architect at Infoblox. In the same way that you can conveniently recognize someone by name instead of government-issued ID or telephone number, the Domain Name System (DNS) provides a convenient means for naming and reaching internet services or resources behind IP addresses. The pervasiveness of DNS, […]

In this post, we demonstrate how to use Amazon Comprehend Medical to extract medication names and medical conditions to monitor drug safety and adverse events. Amazon Comprehend Medical is a natural language processing (NLP) service that uses machine learning (ML) to easily extract relevant medical information from unstructured text. We query the OpenFDA API (an open-source API published by […]

­ This is a guest post by AWS Machine Learning Hero Cyrus Wong. Staying connected with family, friends, and colleagues is easy for most people who live with or close to others. For educators who need to communicate lessons and schedules with their students, or businesses who communicate with new and existing customers, staying connected […]

November 2022: The solution described here is not the latest best practice. The new HuggingFace Deep Learning Container (DLC) is available in Amazon SageMaker (see Use Hugging Face with Amazon SageMaker). For customer training BERT models, the recommended pattern is to use HuggingFace DLC, shown as in Finetuning Hugging Face DistilBERT with Amazon Reviews Polarity dataset. […]