Tag: Amazon Sagemaker

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.

The maturing of artificial intelligence (AI) has brought ready-made services that organizations can use, not only to automate data entry work but also to apply intelligence into the business process. Using modern AI capabilities on AWS, organizations can transform approaches to document management. This allows public sector organizations to save time (enabling faster throughput especially during higher volume paperwork times), so they can help get constituents their services faster, and focus on the most valuable work of the high-touch or high-need cases. Document automation helps reduce human entry error and provide backup services in case of natural disaster.

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.