Tag: Amazon Sagemaker

The Urban Analytics Lab at the National University of Singapore (NUS) spearheads research in geospatial data analysis and 3D city modelling. The lab’s work underpins the development of smart cities and provides scientists, architects, urban planners, and real estate developers with data insights. These insights help parties make informed decisions about projects ranging from energy modelling to urban farming. To meet rising global demand for its data analytics and planning tools, Urban Analytics Lab turned to Amazon Web Services (AWS).

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.

Data is at the heart of healthcare, but our wellbeing is complex. It is a challenge to find the right approach when analyzing or visualizing data. Technology like text-to-speech, augmented reality (AR), and deep learning can help us better understand and explain health data. By designing solutions in the cloud, we can leverage AWS to launch and scale helpful tools as needed, paying for only what we use while keeping data secure.

The cloud can help researchers process complex workloads, store and analyze enormous amounts of data, collaborate globally, and accelerate research and innovation. For research IT, Amazon Web Services (AWS) can help build scalable, cost-effective, and flexible environments while still maintaining the governance and guardrails for security and compliance. Following best practices, AWS allows for centralized management of resources, improved security and compliance of research workloads, and can save costs and accelerate innovation. What are some common questions from research IT customers?

Today, Amazon Web Services (AWS) announced Service Workbench on AWS, a web portal for researchers to deploy domain-specific data and tools on secure IT environments in minutes not months. Customers can accelerate research while promoting repeatability, multi-site collaboration, and cost transparency in the research process. Tailored for researchers, Service Workbench helps quickly and securely stand up research environments for their work, allowing them to focus on the research not the technology.

AWS EdStart Members and founders—Tan Han Sing, founder of Tueetor, and Sanjay Srivastava, founder of Vocareum—are making educational resources more accessible to students at scale. Han Sing is focused on affordably connecting learners from all backgrounds with trainers, while Sanjay is focused on closing the global digital skills gap by providing turnkey virtual labs for higher education, tech training, demo, and assessment.

The University of Illinois Urbana-Champaign (UIUC) believes that technology is a powerful tool for driving results and innovation on campus. Their chief information officer, Mark Henderson, developed a task force—called the Data and Technology Innovation Lab—to identify department challenges and task individuals to build innovative solutions using technology. One area where UIUC identified an opportunity was sports analytics using machine learning (ML). Learn more about how UIUC was inspired by what they were seeing in professional sports, using data to shift their approach to coaching football.

Cancer Commons is a nonprofit network of patients, physicians, and scientists dedicated to helping patients identify and access the best personalized treatment options. Erika Vial Monteverdi, executive director of Cancer Commons, describes how the AWS compute infrastructure, combined with services like Amazon Comprehend Medical, enable physicians and patients to leverage the collective knowledge of the world’s top institutions. 

Research computing has come a long way from the mainframes of the 1960s. At the recent Practice and Experience in Advanced Research Computing (PEARC) conference, I noted four emerging themes that underscore how the field continues to evolve.

In June, Australian startup and AWS EdStart Member Dystech, launched the world’s first screening app for dyslexia and motor dysgraphia. Dyslexia and dysgraphia impact between 10-20 percent of individuals worldwide. With this release, Dystech has the opportunity to change lives and accelerate testing for millions of individuals around globe. Dystech uses artificial intelligence (AI) and machine learning (ML) to create an app that transforms how education and healthcare organizations screen for this disorder.