Category: Amazon SageMaker

A research team led by Dr. Beatriz Martinez Lopez at UC Davis supports pig farmers with a data analytics platform that aggregates and analyzes animal health data to diagnose animal viruses and diseases. But this platform was primarily designed for analysts and data scientists. To truly transform animal disease management, Martinez-Lopez wants to put this data analytics tool into the hands of farmers around the world. So the research team is using the scalable, cost-effective tools of the AWS Cloud, along with a research grant letter of support from AWS, to make this optimized platform a reality.

This fall, artist Suchi Reddy and Amazon Web Services (AWS), in collaboration with the Smithsonian FUTURES Exhibition, debuted me+you in Washington, DC, which embodies the collective answers to the question, “What do you want your future to look like?” me+you is an interactive work of art powered by artificial intelligence (AI) and machine learning (ML) and is the centerpiece of the Smithsonian FUTURES exhibition.

Since 2003, the US federal government has made approximately $1.7 trillion in improper payments, with an estimated $206 billion made in FY 2020 alone. Improper payments are now anticipated to increase proportionally to new levels of federal spending. How can agencies fight improper payments at this scale? And what tools can agencies use to address fraud, erroneous data submission and other causes of this problem? Agencies can use AWS to solve the multi-sided issues of payment integrity.

Using AWS, Edunation seamlessly responded to increasing demand during the COVID-19 pandemic. Edunation collaborates with top educational institutions across the Middle East and North Africa (MENA) region and provides all-in-one learning and school management solutions. Today, the EdTech is on a mission to push learning management systems (LMS) beyond virtual classrooms.

To help protect investments on ML, government organizations can securely store ML source code. Storing Amazon SageMaker Studio code in an AWS CodeCommit repository enables you to keep them as standalone documents to reuse in the future. SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps required to prepare data and build, train, and deploy models. Read on to learn the steps to configure a git-based repository on CodeCommit to manage ML code developed with SageMaker.

Academic medical centers (AMCs) are under pressure to reduce costs, innovate at scale, and improve operational performance. To do this, they’re turning to the cloud. Two AWS Partner Network (APN) Public Sector Partners used the cloud to create solutions for AMCs that use large datasets to help advance medical research and analyze genomic data. Learn how these two partners are building solutions in the cloud to help AMCs further their mission.